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ORCIDRuslan Salakhutdinov
Russ Salakhutdinov
Person information
- affiliation: Carnegie Mellon University, Machine Learning Department, Pittsburgh, PA, USA
- affiliation: University of Toronto, Departments of Statistics and Computer Science, ON, Canada
- affiliation: Massachusetts Institute of Technology, Artificial Intelligence Lab, Cambridge, MA, USA
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Books and Theses
- 2010
[b1]Ruslan Salakhutdinov:
Learning Deep Generative Models. University of Toronto, Canada, 2010
Journal Articles
- 2023
- [j12]Paul Pu Liang, Yiwei Lyu, Xiang Fan, Arav Agarwal
, Yun Cheng, Louis-Philippe Morency, Ruslan Salakhutdinov:
MultiZoo and MultiBench: A Standardized Toolkit for Multimodal Deep Learning. J. Mach. Learn. Res. 24: 234:1-234:7 (2023) - [j11]Yao-Yuan Yang, Cyrus Rashtchian, Ruslan Salakhutdinov, Kamalika Chaudhuri:
Probing Predictions on OOD Images via Nearest Categories. Trans. Mach. Learn. Res. 2023 (2023) - 2021
- [j10]Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, Kushal Lakhotia, Ruslan Salakhutdinov, Abdelrahman Mohamed:
HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units. IEEE ACM Trans. Audio Speech Lang. Process. 29: 3451-3460 (2021) - 2019
- [j9]Andrew Pavlo, Matthew Butrovich, Ananya Joshi, Lin Ma, Prashanth Menon, Dana Van Aken, Lisa Lee, Ruslan Salakhutdinov:
External vs. Internal: An Essay on Machine Learning Agents for Autonomous Database Management Systems. IEEE Data Eng. Bull. 42(2): 32-46 (2019) - 2014
- [j8]Nitish Srivastava, Geoffrey E. Hinton, Alex Krizhevsky, Ilya Sutskever, Ruslan Salakhutdinov:
Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15(1): 1929-1958 (2014) - [j7]Nitish Srivastava, Ruslan Salakhutdinov:
Multimodal learning with deep Boltzmann machines. J. Mach. Learn. Res. 15(1): 2949-2980 (2014) - [j6]R. Devon Hjelm, Vince D. Calhoun, Ruslan Salakhutdinov, Elena A. Allen, Tülay Adali, Sergey M. Plis:
Restricted Boltzmann machines for neuroimaging: An application in identifying intrinsic networks. NeuroImage 96: 245-260 (2014) - 2013
- [j5]Samy Bengio, Li Deng, Hugo Larochelle, Honglak Lee, Ruslan Salakhutdinov:
Guest Editors' Introduction: Special Section on Learning Deep Architectures. IEEE Trans. Pattern Anal. Mach. Intell. 35(8): 1795-1797 (2013) - [j4]Ruslan Salakhutdinov, Joshua B. Tenenbaum, Antonio Torralba:
Learning with Hierarchical-Deep Models. IEEE Trans. Pattern Anal. Mach. Intell. 35(8): 1958-1971 (2013) - 2012
- [j3]Ruslan Salakhutdinov, Geoffrey E. Hinton:
An Efficient Learning Procedure for Deep Boltzmann Machines. Neural Comput. 24(8): 1967-2006 (2012) - 2011
- [j2]Geoffrey E. Hinton, Ruslan Salakhutdinov:
Discovering Binary Codes for Documents by Learning Deep Generative Models. Top. Cogn. Sci. 3(1): 74-91 (2011) - 2009
- [j1]Ruslan Salakhutdinov, Geoffrey E. Hinton:
Semantic hashing. Int. J. Approx. Reason. 50(7): 969-978 (2009)
Conference and Workshop Papers
- 2023
- [c225]Rohan Pandey, Rulin Shao, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency:
Cross-modal Attention Congruence Regularization for Vision-Language Relation Alignment. ACL (1) 2023: 5444-5455 - [c224]Xiang Fan, Yiwei Lyu, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency:
Nano: Nested Human-in-the-Loop Reward Learning for Few-shot Language Model Control. ACL (Findings) 2023: 11970-11992 - [c223]Paul Pu Liang, Yiwei Lyu, Gunjan Chhablani, Nihal Jain, Zihao Deng, Xingbo Wang, Louis-Philippe Morency, Ruslan Salakhutdinov:
MultiViz: Towards User-Centric Visualizations and Interpretations of Multimodal Models. CHI Extended Abstracts 2023: 214:1-214:21 - [c222]Murtaza Dalal, Ajay Mandlekar, Caelan Reed Garrett, Ankur Handa, Ruslan Salakhutdinov, Dieter Fox:
Imitating Task and Motion Planning with Visuomotor Transformers. CoRL 2023: 2565-2593 - [c221]Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Russ Salakhutdinov:
Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective. ICLR 2023 - [c220]Paul Pu Liang, Yiwei Lyu, Gunjan Chhablani, Nihal Jain, Zihao Deng, Xingbo Wang, Louis-Philippe Morency, Ruslan Salakhutdinov:
MultiViz: Towards Visualizing and Understanding Multimodal Models. ICLR 2023 - [c219]Haitian Sun, William W. Cohen, Ruslan Salakhutdinov:
Scenario-based Question Answering with Interacting Contextual Properties. ICLR 2023 - [c218]Brandon Trabucco, Gunnar A. Sigurdsson, Robinson Piramuthu, Gaurav S. Sukhatme, Ruslan Salakhutdinov:
A Simple Approach for Visual Room Rearrangement: 3D Mapping and Semantic Search. ICLR 2023 - [c217]Paul Pu Liang, Yun Cheng, Ruslan Salakhutdinov, Louis-Philippe Morency:
Multimodal Fusion Interactions: A Study of Human and Automatic Quantification. ICMI 2023: 425-435 - [c216]Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov:
A Connection between One-Step RL and Critic Regularization in Reinforcement Learning. ICML 2023: 9485-9507 - [c215]Jing Yu Koh, Ruslan Salakhutdinov, Daniel Fried:
Grounding Language Models to Images for Multimodal Inputs and Outputs. ICML 2023: 17283-17300 - [c214]Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Russ Salakhutdinov:
Graph Generative Model for Benchmarking Graph Neural Networks. ICML 2023: 40175-40198 - [c213]So Yeon Min, Yao-Hung Hubert Tsai, Wei Ding, Ali Farhadi, Ruslan Salakhutdinov, Yonatan Bisk, Jian Zhang:
Self-Supervised Object Goal Navigation with In-Situ Finetuning. IROS 2023: 7119-7126 - [c212]Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn:
Contrastive Example-Based Control. L4DC 2023: 155-169 - [c211]Jing Yu Koh, Daniel Fried, Russ Salakhutdinov:
Generating Images with Multimodal Language Models. NeurIPS 2023 - [c210]Paul Pu Liang, Yun Cheng, Xiang Fan, Chun Kai Ling, Suzanne Nie, Richard J. Chen, Zihao Deng, Nicholas B. Allen, Randy Auerbach, Faisal Mahmood, Russ Salakhutdinov, Louis-Philippe Morency:
Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework. NeurIPS 2023 - [c209]Paul Pu Liang, Zihao Deng, Martin Q. Ma, James Y. Zou, Louis-Philippe Morency, Ruslan Salakhutdinov:
Factorized Contrastive Learning: Going Beyond Multi-view Redundancy. NeurIPS 2023 - [c208]Yue Wu, So Yeon Min, Shrimai Prabhumoye, Yonatan Bisk, Russ Salakhutdinov, Amos Azaria, Tom M. Mitchell, Yuanzhi Li:
SPRING: Studying Papers and Reasoning to play Games. NeurIPS 2023 - 2022
- [c207]Yanan Zheng, Jing Zhou, Yujie Qian, Ming Ding, Chonghua Liao, Li Jian, Ruslan Salakhutdinov, Jie Tang, Sebastian Ruder, Zhilin Yang:
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding. ACL (1) 2022: 501-516 - [c206]Haitian Sun, William W. Cohen, Ruslan Salakhutdinov:
ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers. ACL (1) 2022: 3627-3637 - [c205]Yiwei Lyu, Paul Pu Liang, Zihao Deng, Ruslan Salakhutdinov, Louis-Philippe Morency:
DIME: Fine-grained Interpretations of Multimodal Models via Disentangled Local Explanations. AIES 2022: 455-467 - [c204]Samuel Yu, Peter Wu, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency:
PACS: A Dataset for Physical Audiovisual CommonSense Reasoning. ECCV (37) 2022: 292-309 - [c203]Yuxin Xiao, Paul Pu Liang, Umang Bhatt, Willie Neiswanger, Ruslan Salakhutdinov, Louis-Philippe Morency:
Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis. EMNLP (Findings) 2022: 7273-7284 - [c202]So Yeon Min, Hao Zhu, Ruslan Salakhutdinov, Yonatan Bisk:
Don't Copy the Teacher: Data and Model Challenges in Embodied Dialogue. EMNLP 2022: 9361-9368 - [c201]Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
The Information Geometry of Unsupervised Reinforcement Learning. ICLR 2022 - [c200]So Yeon Min, Devendra Singh Chaplot, Pradeep Kumar Ravikumar, Yonatan Bisk, Ruslan Salakhutdinov:
FILM: Following Instructions in Language with Modular Methods. ICLR 2022 - [c199]Yao-Hung Hubert Tsai, Tianqin Li, Weixin Liu, Peiyuan Liao, Ruslan Salakhutdinov, Louis-Philippe Morency:
Learning Weakly-supervised Contrastive Representations. ICLR 2022 - [c198]Yao-Hung Hubert Tsai, Tianqin Li, Martin Q. Ma, Han Zhao, Kun Zhang, Louis-Philippe Morency, Ruslan Salakhutdinov:
Conditional Contrastive Learning with Kernel. ICLR 2022 - [c197]Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez:
C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks. ICLR 2022 - [c196]Tianwei Ni, Benjamin Eysenbach, Ruslan Salakhutdinov:
Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs. ICML 2022: 16691-16723 - [c195]Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov:
Mismatched No More: Joint Model-Policy Optimization for Model-Based RL. NeurIPS 2022 - [c194]Benjamin Eysenbach, Soumith Udatha, Russ Salakhutdinov, Sergey Levine:
Imitating Past Successes can be Very Suboptimal. NeurIPS 2022 - [c193]Benjamin Eysenbach, Tianjun Zhang, Sergey Levine, Ruslan Salakhutdinov:
Contrastive Learning as Goal-Conditioned Reinforcement Learning. NeurIPS 2022 - [c192]Cheng-Fu Yang, Yao-Hung Hubert Tsai, Wan-Cyuan Fan, Russ Salakhutdinov, Louis-Philippe Morency, Frank Wang:
Paraphrasing Is All You Need for Novel Object Captioning. NeurIPS 2022 - [c191]Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi:
Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks. NeurIPS 2022 - [c190]Mathis Petrovich, Chao Liang, Ryoma Sato, Yanbin Liu, Yao-Hung Hubert Tsai, Linchao Zhu, Yi Yang, Ruslan Salakhutdinov, Makoto Yamada:
Feature-Robust Optimal Transport for High-Dimensional Data. ECML/PKDD (5) 2022: 291-307 - 2021
- [c189]Ryan Mohr, Allan M. Avila, Soham Ghosh, Ananta Bhattarai, Muqiao Yang, Xintian Feng, Martin Head-Gordon, Ruslan Salakhutdinov, Maria Fonoberova, Igor Mezic:
Combining Programmable Potentials and Neural Networks for Materials Problems. AAAI Spring Symposium: MLPS 2021 - [c188]Paul Pu Liang, Terrance Liu, Anna Cai, Michal Muszynski, Ryo Ishii, Nicholas B. Allen, Randy Auerbach, David Brent, Ruslan Salakhutdinov, Louis-Philippe Morency:
Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data. ACL/IJCNLP (1) 2021: 4170-4187 - [c187]Peter Wu, Paul Pu Liang, Jiatong Shi, Ruslan Salakhutdinov, Shinji Watanabe, Louis-Philippe Morency:
Understanding the Tradeoffs in Client-side Privacy for Downstream Speech Tasks. APSIPA ASC 2021: 841-848 - [c186]Wei-Ning Hsu, Yao-Hung Hubert Tsai, Benjamin Bolte, Ruslan Salakhutdinov, Abdelrahman Mohamed:
Hubert: How Much Can a Bad Teacher Benefit ASR Pre-Training? ICASSP 2021: 6533-6537 - [c185]Liangke Gui, Adrien Bardes, Ruslan Salakhutdinov, Alexander Hauptmann, Martial Hebert, Yu-Xiong Wang:
Learning to Hallucinate Examples from Extrinsic and Intrinsic Supervision. ICCV 2021: 8681-8691 - [c184]Benjamin Eysenbach, Shreyas Chaudhari, Swapnil Asawa, Sergey Levine, Ruslan Salakhutdinov:
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers. ICLR 2021 - [c183]Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
C-Learning: Learning to Achieve Goals via Recursive Classification. ICLR 2021 - [c182]Emilio Parisotto, Ruslan Salakhutdinov:
Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation. ICLR 2021 - [c181]Yao-Hung Hubert Tsai, Yue Wu, Ruslan Salakhutdinov, Louis-Philippe Morency:
Self-supervised Learning from a Multi-view Perspective. ICLR 2021 - [c180]Yao-Hung Hubert Tsai, Martin Q. Ma, Muqiao Yang, Han Zhao, Louis-Philippe Morency, Ruslan Salakhutdinov:
Self-supervised Representation Learning with Relative Predictive Coding. ICLR 2021 - [c179]Russ Salakhutdinov:
From Differentiable Reasoning to Self-supervised Embodied Active Learning. ICMI 2021: 5 - [c178]Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, J. Zico Kolter, Zachary C. Lipton, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Pradeep Ravikumar:
On Proximal Policy Optimization's Heavy-tailed Gradients. ICML 2021: 3610-3619 - [c177]Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, Ruslan Salakhutdinov:
Towards Understanding and Mitigating Social Biases in Language Models. ICML 2021: 6565-6576 - [c176]Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi S. Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov:
Information Obfuscation of Graph Neural Networks. ICML 2021: 6600-6610 - [c175]Haitian Sun, Patrick Verga, Bhuwan Dhingra, Ruslan Salakhutdinov, William W. Cohen:
Reasoning Over Virtual Knowledge Bases With Open Predicate Relations. ICML 2021: 9966-9977 - [c174]Ruosong Wang, Yifan Wu, Ruslan Salakhutdinov, Sham M. Kakade:
Instabilities of Offline RL with Pre-Trained Neural Representation. ICML 2021: 10948-10960 - [c173]Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh:
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning. ICML 2021: 11319-11328 - [c172]Shruti Palaskar, Ruslan Salakhutdinov, Alan W. Black, Florian Metze:
Multimodal Speech Summarization Through Semantic Concept Learning. Interspeech 2021: 791-795 - [c171]Paul Pu Liang, Peter Wu, Ziyin Liu, Louis-Philippe Morency, Ruslan Salakhutdinov:
Cross-Modal Generalization: Learning in Low Resource Modalities via Meta-Alignment. ACM Multimedia 2021: 2680-2689 - [c170]Yiwei Lyu, Paul Pu Liang, Hai Pham, Eduard H. Hovy, Barnabás Póczos, Ruslan Salakhutdinov, Louis-Philippe Morency:
StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer. NAACL-HLT 2021: 2116-2138 - [c169]Shrimai Prabhumoye, Brendon Boldt, Ruslan Salakhutdinov, Alan W. Black:
Case Study: Deontological Ethics in NLP. NAACL-HLT 2021: 3784-3798 - [c168]Shrimai Prabhumoye, Kazuma Hashimoto, Yingbo Zhou, Alan W. Black, Ruslan Salakhutdinov:
Focused Attention Improves Document-Grounded Generation. NAACL-HLT 2021: 4274-4287 - [c167]Ben Eysenbach, Sergey Levine, Ruslan Salakhutdinov:
Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification. NeurIPS 2021: 11541-11552 - [c166]Devendra Singh Chaplot, Murtaza Dalal, Saurabh Gupta, Jitendra Malik, Ruslan Salakhutdinov:
SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency. NeurIPS 2021: 13086-13098 - [c165]Murtaza Dalal, Deepak Pathak, Ruslan Salakhutdinov:
Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives. NeurIPS 2021: 21847-21859 - [c164]Ben Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
Robust Predictable Control. NeurIPS 2021: 27813-27825 - [c163]Paul Pu Liang, Yiwei Lyu, Xiang Fan, Zetian Wu, Yun Cheng, Jason Wu, Leslie Chen, Peter Wu, Michelle A. Lee, Yuke Zhu, Ruslan Salakhutdinov, Louis-Philippe Morency:
MultiBench: Multiscale Benchmarks for Multimodal Representation Learning. NeurIPS Datasets and Benchmarks 2021 - [c162]Yanbin Liu, Makoto Yamada, Yao-Hung Hubert Tsai, Tam Le, Ruslan Salakhutdinov, Yi Yang:
LSMI-Sinkhorn: Semi-supervised Mutual Information Estimation with Optimal Transport. ECML/PKDD (1) 2021: 655-670 - 2020
- [c161]Aman Madaan, Amrith Setlur, Tanmay Parekh, Barnabás Póczos, Graham Neubig, Yiming Yang, Ruslan Salakhutdinov, Alan W. Black, Shrimai Prabhumoye:
Politeness Transfer: A Tag and Generate Approach. ACL 2020: 1869-1881 - [c160]Shrimai Prabhumoye, Ruslan Salakhutdinov, Alan W. Black:
Topological Sort for Sentence Ordering. ACL 2020: 2783-2792 - [c159]Paul Pu Liang, Irene Mengze Li, Emily Zheng, Yao Chong Lim, Ruslan Salakhutdinov, Louis-Philippe Morency:
Towards Debiasing Sentence Representations. ACL 2020: 5502-5515 - [c158]Paul Pu Liang, Jeffrey Chen, Ruslan Salakhutdinov, Louis-Philippe Morency, Satwik Kottur:
On Emergent Communication in Competitive Multi-Agent Teams. AAMAS 2020: 735-743 - [c157]Shrimai Prabhumoye, Alan W. Black, Ruslan Salakhutdinov:
Exploring Controllable Text Generation Techniques. COLING 2020: 1-14 - [c156]Devendra Singh Chaplot, Ruslan Salakhutdinov, Abhinav Gupta, Saurabh Gupta:
Neural Topological SLAM for Visual Navigation. CVPR 2020: 12872-12881 - [c155]Yao-Hung Hubert Tsai, Martin Ma, Muqiao Yang, Ruslan Salakhutdinov, Louis-Philippe Morency:
Multimodal Routing: Improving Local and Global Interpretability of Multimodal Language Analysis. EMNLP (1) 2020: 1823-1833 - [c154]Muqiao Yang, Martin Q. Ma, Dongyu Li, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov:
Complex Transformer: A Framework for Modeling Complex-Valued Sequence. ICASSP 2020: 4232-4236 - [c153]Sanjeev Arora, Simon S. Du, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang, Dingli Yu:
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks. ICLR 2020 - [c152]Devendra Singh Chaplot, Dhiraj Gandhi, Saurabh Gupta, Abhinav Gupta, Ruslan Salakhutdinov:
Learning To Explore Using Active Neural SLAM. ICLR 2020 - [c151]Bhuwan Dhingra, Manzil Zaheer, Vidhisha Balachandran, Graham Neubig, Ruslan Salakhutdinov, William W. Cohen:
Differentiable Reasoning over a Virtual Knowledge Base. ICLR 2020 - [c150]Yao-Hung Hubert Tsai, Nitish Srivastava, Hanlin Goh, Ruslan Salakhutdinov:
Capsules with Inverted Dot-Product Attention Routing. ICLR 2020 - [c149]Devendra Singh Chaplot, Lisa Lee, Ruslan Salakhutdinov, Devi Parikh, Dhruv Batra:
Embodied Multimodal Multitask Learning. IJCAI 2020: 2442-2448 - [c148]Devendra Singh Chaplot, Dhiraj Gandhi, Abhinav Gupta, Ruslan Salakhutdinov:
Object Goal Navigation using Goal-Oriented Semantic Exploration. NeurIPS 2020 - [c147]Ben Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov:
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement. NeurIPS 2020 - [c146]Lisa Lee, Ben Eysenbach, Ruslan Salakhutdinov, Shixiang Shane Gu, Chelsea Finn:
Weakly-Supervised Reinforcement Learning for Controllable Behavior. NeurIPS 2020 - [c145]Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov:
Neural Methods for Point-wise Dependency Estimation. NeurIPS 2020 - [c144]Ruosong Wang, Simon S. Du, Lin F. Yang, Ruslan Salakhutdinov:
On Reward-Free Reinforcement Learning with Linear Function Approximation. NeurIPS 2020 - [c143]Ruosong Wang, Ruslan Salakhutdinov, Lin F. Yang:
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension. NeurIPS 2020 - [c142]Ruosong Wang, Peilin Zhong, Simon S. Du, Ruslan Salakhutdinov, Lin F. Yang:
Planning with General Objective Functions: Going Beyond Total Rewards. NeurIPS 2020 - [c141]Yao-Yuan Yang, Cyrus Rashtchian, Hongyang Zhang, Ruslan Salakhutdinov, Kamalika Chaudhuri:
A Closer Look at Accuracy vs. Robustness. NeurIPS 2020 - 2019
- [c140]Devendra Singh Sachan, Manzil Zaheer, Ruslan Salakhutdinov:
Revisiting LSTM Networks for Semi-Supervised Text Classification via Mixed Objective Function. AAAI 2019: 6940-6948 - [c139]Paul Pu Liang, Zhun Liu, Yao-Hung Hubert Tsai, Qibin Zhao, Ruslan Salakhutdinov, Louis-Philippe Morency:
Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization. ACL (1) 2019: 1569-1576 - [c138]Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc Viet Le, Ruslan Salakhutdinov:
Transformer-XL: Attentive Language Models beyond a Fixed-Length Context. ACL (1) 2019: 2978-2988 - [c137]Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang, J. Zico Kolter, Louis-Philippe Morency, Ruslan Salakhutdinov:
Multimodal Transformer for Unaligned Multimodal Language Sequences. ACL (1) 2019: 6558-6569 - [c136]Hongyang Zhang, Junru Shao, Ruslan Salakhutdinov:
Deep Neural Networks with Multi-Branch Architectures Are Intrinsically Less Non-Convex. AISTATS 2019: 1099-1109 - [c135]Yichuan Charlie Tang, Jian Zhang, Ruslan Salakhutdinov:
Worst Cases Policy Gradients. CoRL 2019: 1078-1093 - [c134]Yao-Hung Hubert Tsai, Santosh Kumar Divvala, Louis-Philippe Morency, Ruslan Salakhutdinov, Ali Farhadi:
Video Relationship Reasoning Using Gated Spatio-Temporal Energy Graph. CVPR 2019: 10424-10433 - [c133]Yao-Hung Hubert Tsai, Shaojie Bai, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov:
Transformer Dissection: An Unified Understanding for Transformer's Attention via the Lens of Kernel. EMNLP/IJCNLP (1) 2019: 4343-4352 - [c132]Chun-Liang Li, Manzil Zaheer, Yang Zhang, Barnabás Póczos, Ruslan Salakhutdinov:
Point Cloud GAN. DGS@ICLR 2019 - [c131]Bowen Tan, Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing:
Connecting the Dots Between MLE and RL for Sequence Generation. DeepRLStructPred@ICLR 2019 - [c130]Yao-Hung Hubert Tsai, Paul Pu Liang, Amir Zadeh, Louis-Philippe Morency, Ruslan Salakhutdinov:
Learning Factorized Multimodal Representations. ICLR (Poster) 2019 - [c129]Haowen Xu, Hao Zhang, Zhiting Hu, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing:
AutoLoss: Learning Discrete Schedule for Alternate Optimization. ICLR (Poster) 2019 - [c128]Makoto Yamada, Denny Wu, Yao-Hung Hubert Tsai, Hirofumi Ohta, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu:
Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator. ICLR (Poster) 2019 - [c127]William H. Guss, Brandon Houghton, Nicholay Topin, Phillip Wang, Cayden Codel, Manuela Veloso, Ruslan Salakhutdinov:
MineRL: A Large-Scale Dataset of Minecraft Demonstrations. IJCAI 2019: 2442-2448 - [c126]Ruslan Salakhutdinov:
Integrating Domain-Knowledge into Deep Learning. KDD 2019: 3176 - [c125]Paul Pu Liang, Yao Chong Lim, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov, Louis-Philippe Morency:
Strong and Simple Baselines for Multimodal Utterance Embeddings. NAACL-HLT (1) 2019: 2599-2609 - [c124]Simon S. Du, Kangcheng Hou, Ruslan Salakhutdinov, Barnabás Póczos, Ruosong Wang, Keyulu Xu:
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels. NeurIPS 2019: 5724-5734 - [c123]Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, Quoc V. Le:
XLNet: Generalized Autoregressive Pretraining for Language Understanding. NeurIPS 2019: 5754-5764 - [c122]Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang:
On Exact Computation with an Infinitely Wide Neural Net. NeurIPS 2019: 8139-8148 - [c121]Ziyin Liu, Zhikang Wang, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency, Masahito Ueda:
Deep Gamblers: Learning to Abstain with Portfolio Theory. NeurIPS 2019: 10622-10632 - [c120]Han Zhao, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov, Geoffrey J. Gordon:
Learning Neural Networks with Adaptive Regularization. NeurIPS 2019: 11389-11400 - [c119]Ben Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning. NeurIPS 2019: 15220-15231 - [c118]Yichuan Charlie Tang, Ruslan Salakhutdinov:
Multiple Futures Prediction. NeurIPS 2019: 15398-15408 - [c117]Zhiting Hu, Bowen Tan, Ruslan Salakhutdinov, Tom M. Mitchell, Eric P. Xing:
Learning Data Manipulation for Augmentation and Weighting. NeurIPS 2019: 15738-15749 - [c116]Zhilin Yang, Thang Luong, Ruslan Salakhutdinov, Quoc V. Le:
Mixtape: Breaking the Softmax Bottleneck Efficiently. NeurIPS 2019: 15922-15930 - 2018
- [c115]Devendra Singh Chaplot, Kanthashree Mysore Sathyendra, Rama Kumar Pasumarthi, Dheeraj Rajagopal, Ruslan Salakhutdinov:
Gated-Attention Architectures for Task-Oriented Language Grounding. AAAI 2018: 2819-2826 - [c114]Devendra Singh Chaplot, Ruslan Salakhutdinov:
Knowledge-based Word Sense Disambiguation using Topic Models. AAAI 2018: 5062-5069 - [c113]Shrimai Prabhumoye, Yulia Tsvetkov, Ruslan Salakhutdinov, Alan W. Black:
Style Transfer Through Back-Translation. ACL (1) 2018: 866-876 - [c112]Devendra Singh Chaplot, Christopher MacLellan, Ruslan Salakhutdinov, Kenneth R. Koedinger:
Learning Cognitive Models Using Neural Networks. AIED (1) 2018: 43-56 - [c111]Sashank J. Reddi, Manzil Zaheer, Suvrit Sra, Barnabás Póczos, Francis R. Bach, Ruslan Salakhutdinov, Alexander J. Smola:
A Generic Approach for Escaping Saddle points. AISTATS 2018: 1233-1242 - [c110]Devendra Singh Sachan, Manzil Zaheer, Ruslan Salakhutdinov:
Investigating the Working of Text Classifiers. COLING 2018: 2120-2131 - [c109]Emilio Parisotto, Devendra Singh Chaplot, Jian Zhang, Ruslan Salakhutdinov:
Global Pose Estimation With an Attention-Based Recurrent Network. CVPR Workshops 2018: 237-246 - [c108]Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, Christopher D. Manning:
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering. EMNLP 2018: 2369-2380 - [c107]Haitian Sun, Bhuwan Dhingra, Manzil Zaheer, Kathryn Mazaitis, Ruslan Salakhutdinov, William W. Cohen:
Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text. EMNLP 2018: 4231-4242 - [c106]Devendra Singh Chaplot, Emilio Parisotto, Ruslan Salakhutdinov:
Active Neural Localization. ICLR (Poster) 2018 - [c105]Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing:
On Unifying Deep Generative Models. ICLR (Poster) 2018 - [c104]Lisa Lee, Emilio Parisotto, Devendra Singh Chaplot, Ruslan Salakhutdinov:
LSTM Iteration Networks: An Exploration of Differentiable Path Finding. ICLR (Workshop) 2018 - [c103]Emilio Parisotto, Ruslan Salakhutdinov:
Neural Map: Structured Memory for Deep Reinforcement Learning. ICLR (Poster) 2018 - [c102]Yao-Hung Hubert Tsai, Denny Wu, Makoto Yamada, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu:
Selecting the Best in GANs Family: a Post Selection Inference Framework. ICLR (Workshop) 2018 - [c101]Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov, William W. Cohen:
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model. ICLR 2018 - [c100]Lisa Lee, Emilio Parisotto, Devendra Singh Chaplot, Eric P. Xing, Ruslan Salakhutdinov:
Gated Path Planning Networks. ICML 2018: 2953-2961 - [c99]Junier B. Oliva, Avinava Dubey, Manzil Zaheer, Barnabás Póczos, Ruslan Salakhutdinov, Eric P. Xing, Jeff Schneider:
Transformation Autoregressive Networks. ICML 2018: 3895-3904 - [c98]Mario Srouji, Jian Zhang, Ruslan Salakhutdinov:
Structured Control Nets for Deep Reinforcement Learning. ICML 2018: 4749-4758 - [c97]Bhuwan Dhingra, Qiao Jin, Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov:
Neural Models for Reasoning over Multiple Mentions Using Coreference. NAACL-HLT (2) 2018: 42-48 - [c96]Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh:
How Many Samples are Needed to Estimate a Convolutional Neural Network? NeurIPS 2018: 371-381 - [c95]Zhilin Yang, Junbo Jake Zhao, Bhuwan Dhingra, Kaiming He, William W. Cohen, Ruslan Salakhutdinov, Yann LeCun:
GLoMo: Unsupervised Learning of Transferable Relational Graphs. NeurIPS 2018: 8964-8975 - [c94]Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Lianhui Qin, Xiaodan Liang, Haoye Dong, Eric P. Xing:
Deep Generative Models with Learnable Knowledge Constraints. NeurIPS 2018: 10522-10533 - [c93]Jia Chen, Shizhe Chen, Qin Jin, Alexander G. Hauptmann, Po-Yao Huang, Junwei Liang, Vaibhav, Xiaojun Chang, Jiang Liu, Ting-Yao Hu, Wenhe Liu, Wei Ke, Wayner Barrios, Haroon Idrees, Donghyun Yoo, Yaser Sheikh, Ruslan Salakhutdinov, Kris Kitani, Dong Huang:
Informedia @ TRECVID 2018: Ad-hoc Video Search, Video to Text Description, Activities in Extended video. TRECVID 2018 - 2017
- [c92]Zhilin Yang, Junjie Hu, Ruslan Salakhutdinov, William W. Cohen:
Semi-Supervised QA with Generative Domain-Adaptive Nets. ACL (1) 2017: 1040-1050 - [c91]Bhuwan Dhingra, Hanxiao Liu, Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov:
Gated-Attention Readers for Text Comprehension. ACL (1) 2017: 1832-1846 - [c90]Kenneth Marino, Ruslan Salakhutdinov, Abhinav Gupta:
The More You Know: Using Knowledge Graphs for Image Classification. CVPR 2017: 20-28 - [c89]Michael Figurnov, Maxwell D. Collins, Yukun Zhu, Li Zhang, Jonathan Huang, Dmitry P. Vetrov, Ruslan Salakhutdinov:
Spatially Adaptive Computation Time for Residual Networks. CVPR 2017: 1790-1799 - [c88]Pengtao Xie, Ruslan Salakhutdinov, Luntian Mou, Eric P. Xing:
Deep Determinantal Point Process for Large-Scale Multi-label Classification. ICCV 2017: 473-482 - [c87]Yao-Hung Hubert Tsai, Liang-Kang Huang, Ruslan Salakhutdinov:
Learning Robust Visual-Semantic Embeddings. ICCV 2017: 3591-3600 - [c86]Yuhuai Wu, Yuri Burda, Ruslan Salakhutdinov, Roger B. Grosse:
On the Quantitative Analysis of Decoder-Based Generative Models. ICLR (Poster) 2017 - [c85]Zhilin Yang, Bhuwan Dhingra, Ye Yuan, Junjie Hu, William W. Cohen, Ruslan Salakhutdinov:
Words or Characters? Fine-grained Gating for Reading Comprehension. ICLR (Poster) 2017 - [c84]Zhilin Yang, Ruslan Salakhutdinov, William W. Cohen:
Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks. ICLR (Poster) 2017 - [c83]Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing:
Toward Controlled Generation of Text. ICML 2017: 1587-1596 - [c82]Zichao Yang, Zhiting Hu, Ruslan Salakhutdinov, Taylor Berg-Kirkpatrick:
Improved Variational Autoencoders for Text Modeling using Dilated Convolutions. ICML 2017: 3881-3890 - [c81]Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabás Póczos, Ruslan Salakhutdinov, Alexander J. Smola:
Deep Sets. NIPS 2017: 3391-3401 - [c80]Zihang Dai, Zhilin Yang, Fan Yang, William W. Cohen, Ruslan Salakhutdinov:
Good Semi-supervised Learning That Requires a Bad GAN. NIPS 2017: 6510-6520 - 2016
- [c79]Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing:
Deep Kernel Learning. AISTATS 2016: 370-378 - [c78]Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing:
Deep Neural Networks with Massive Learned Knowledge. EMNLP 2016: 1670-1679 - [c77]Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov:
Revisiting Semi-Supervised Learning with Graph Embeddings. ICML 2016: 40-48 - [c76]Saizheng Zhang, Yuhuai Wu, Tong Che, Zhouhan Lin, Roland Memisevic, Ruslan Salakhutdinov, Yoshua Bengio:
Architectural Complexity Measures of Recurrent Neural Networks. NIPS 2016: 1822-1830 - [c75]Zhilin Yang, Ye Yuan, Yuexin Wu, William W. Cohen, Ruslan Salakhutdinov:
Review Networks for Caption Generation. NIPS 2016: 2361-2369 - [c74]Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing:
Stochastic Variational Deep Kernel Learning. NIPS 2016: 2586-2594 - [c73]Yuhuai Wu, Saizheng Zhang, Ying Zhang, Yoshua Bengio, Ruslan Salakhutdinov:
On Multiplicative Integration with Recurrent Neural Networks. NIPS 2016: 2856-2864 - [c72]Behnam Neyshabur, Yuhuai Wu, Ruslan Salakhutdinov, Nati Srebro:
Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations. NIPS 2016: 3477-3485 - [c71]R. Devon Hjelm, Russ Salakhutdinov, Kyunghyun Cho, Nebojsa Jojic, Vince D. Calhoun, Junyoung Chung:
Iterative Refinement of the Approximate Posterior for Directed Belief Networks. NIPS 2016: 4691-4699 - [c70]Yuri Burda, Roger B. Grosse, Ruslan Salakhutdinov:
Importance Weighted Autoencoders. ICLR (Poster) 2016 - [c69]Elman Mansimov, Emilio Parisotto, Lei Jimmy Ba, Ruslan Salakhutdinov:
Generating Images from Captions with Attention. ICLR 2016 - [c68]Behnam Neyshabur, Ryota Tomioka, Ruslan Salakhutdinov, Nathan Srebro:
Data-Dependent Path Normalization in Neural Networks. ICLR (Poster) 2016 - [c67]Emilio Parisotto, Lei Jimmy Ba, Ruslan Salakhutdinov:
Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning. ICLR (Poster) 2016 - 2015
- [c66]Yuri Burda, Roger B. Grosse, Ruslan Salakhutdinov:
Accurate and conservative estimates of MRF log-likelihood using reverse annealing. AISTATS 2015 - [c65]Shengxin Zha, Florian Luisier, Walter Andrews, Nitish Srivastava, Ruslan Salakhutdinov:
Exploiting Image-trained CNN Architectures for Unconstrained Video Classification. BMVC 2015: 60.1-60.13 - [c64]Yukun Zhu, Raquel Urtasun, Ruslan Salakhutdinov, Sanja Fidler:
segDeepM: Exploiting segmentation and context in deep neural networks for object detection. CVPR 2015: 4703-4711 - [c63]Yukun Zhu, Ryan Kiros, Richard S. Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, Sanja Fidler:
Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books. ICCV 2015: 19-27 - [c62]Lei Jimmy Ba, Kevin Swersky, Sanja Fidler, Ruslan Salakhutdinov:
Predicting Deep Zero-Shot Convolutional Neural Networks Using Textual Descriptions. ICCV 2015: 4247-4255 - [c61]Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov:
Unsupervised Learning of Video Representations using LSTMs. ICML 2015: 843-852 - [c60]Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C. Courville, Ruslan Salakhutdinov, Richard S. Zemel, Yoshua Bengio:
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. ICML 2015: 2048-2057 - [c59]Roger B. Grosse, Ruslan Salakhutdinov:
Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher Matrix. ICML 2015: 2304-2313 - [c58]Behnam Neyshabur, Ruslan Salakhutdinov, Nathan Srebro:
Path-SGD: Path-Normalized Optimization in Deep Neural Networks. NIPS 2015: 2422-2430 - [c57]Jimmy Ba, Ruslan Salakhutdinov, Roger B. Grosse, Brendan J. Frey:
Learning Wake-Sleep Recurrent Attention Models. NIPS 2015: 2593-2601 - [c56]Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov, Richard S. Zemel, Raquel Urtasun, Antonio Torralba, Sanja Fidler:
Skip-Thought Vectors. NIPS 2015: 3294-3302 - 2014
- [c55]Ryan Kiros, Ruslan Salakhutdinov, Richard S. Zemel:
Multimodal Neural Language Models. ICML 2014: 595-603 - [c54]Ruslan Salakhutdinov:
Deep learning. KDD 2014: 1973 - [c53]Yichuan Tang, Nitish Srivastava, Ruslan Salakhutdinov:
Learning Generative Models with Visual Attention. NIPS 2014: 1808-1816 - [c52]Ryan Kiros, Richard S. Zemel, Ruslan Salakhutdinov:
A Multiplicative Model for Learning Distributed Text-Based Attribute Representations. NIPS 2014: 2348-2356 - [c51]Florian Luisier, Manasvi Tickoo, Walter Andrews, Guangnan Ye, Dong Liu, Shih-Fu Chang, Ruslan Salakhutdinov, Vlad I. Morariu, Larry Davis, Abhinav Gupta, Ismail Haritaoglu, Sadiye Guler, Ashutosh Morde:
BBN VISER TRECVID 2014 Multimedia Event Detection and Multimedia Event Recounting Systems. TRECVID 2014 - [c50]Sergey M. Plis, R. Devon Hjelm, Ruslan Salakhutdinov, Vince D. Calhoun:
Deep learning for neuroimaging: a validation study. ICLR (Workshop Poster) 2014 - 2013
- [c49]Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton:
Tensor Analyzers. ICML (3) 2013: 163-171 - [c48]Yichuan Tang, Ruslan Salakhutdinov:
Learning Stochastic Feedforward Neural Networks. NIPS 2013: 530-538 - [c47]Nitish Srivastava, Ruslan Salakhutdinov:
Discriminative Transfer Learning with Tree-based Priors. NIPS 2013: 2094-2102 - [c46]Brenden M. Lake, Ruslan Salakhutdinov, Joshua B. Tenenbaum:
One-shot learning by inverting a compositional causal process. NIPS 2013: 2526-2534 - [c45]Roger B. Grosse, Chris J. Maddison, Ruslan Salakhutdinov:
Annealing between distributions by averaging moments. NIPS 2013: 2769-2777 - [c44]Behnam Neyshabur, Nati Srebro, Ruslan Salakhutdinov, Yury Makarychev, Payman Yadollahpour:
The Power of Asymmetry in Binary Hashing. NIPS 2013: 2823-2831 - [c43]Nitish Srivastava, Ruslan Salakhutdinov, Geoffrey E. Hinton:
Modeling Documents with Deep Boltzmann Machines. UAI 2013 - 2012
- [c42]Brenden M. Lake, Ruslan Salakhutdinov, Joshua B. Tenenbaum:
Concept learning as motor program induction: A large-scale empirical study. CogSci 2012 - [c41]Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton:
Robust Boltzmann Machines for recognition and denoising. CVPR 2012: 2264-2271 - [c40]Yaodong Zhang, Ruslan Salakhutdinov, Hung-An Chang, James R. Glass:
Resource configurable spoken query detection using Deep Boltzmann Machines. ICASSP 2012: 5161-5164 - [c39]Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton:
Deep Mixtures of Factor Analysers. ICML 2012 - [c38]Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton:
Deep Lambertian Networks. ICML 2012 - [c37]Rina Foygel, Nathan Srebro, Ruslan Salakhutdinov:
Matrix reconstruction with the local max norm. NIPS 2012: 944-952 - [c36]Mohammad Norouzi, David J. Fleet, Ruslan Salakhutdinov:
Hamming Distance Metric Learning. NIPS 2012: 1070-1078 - [c35]Nitish Srivastava, Ruslan Salakhutdinov:
Multimodal Learning with Deep Boltzmann Machines. NIPS 2012: 2231-2239 - [c34]Ruslan Salakhutdinov, Geoffrey E. Hinton:
A Better Way to Pretrain Deep Boltzmann Machines. NIPS 2012: 2456-2464 - [c33]Kevin Swersky, Daniel Tarlow, Ilya Sutskever, Ruslan Salakhutdinov, Richard S. Zemel, Ryan P. Adams:
Cardinality Restricted Boltzmann Machines. NIPS 2012: 3302-3310 - [c32]Roger B. Grosse, Ruslan Salakhutdinov, William T. Freeman, Joshua B. Tenenbaum:
Exploiting compositionality to explore a large space of model structures. UAI 2012: 306-315 - [c31]Ruslan Salakhutdinov, Joshua B. Tenenbaum, Antonio Torralba:
One-Shot Learning with a Hierarchical Nonparametric Bayesian Model. ICML Unsupervised and Transfer Learning 2012: 195-206 - [c30]Ruslan Salakhutdinov, Sham M. Kakade, Dean P. Foster:
Domain Adaptation: A Small Sample Statistical Approach. AISTATS 2012: 960-968 - 2011
- [c29]Brenden M. Lake, Ruslan Salakhutdinov, Jason Gross, Joshua B. Tenenbaum:
One shot learning of simple visual concepts. CogSci 2011 - [c28]Ruslan Salakhutdinov, Antonio Torralba, Joshua B. Tenenbaum:
Learning to share visual appearance for multiclass object detection. CVPR 2011: 1481-1488 - [c27]Joseph J. Lim, Ruslan Salakhutdinov, Antonio Torralba:
Transfer Learning by Borrowing Examples for Multiclass Object Detection. NIPS 2011: 118-126 - [c26]Ruslan Salakhutdinov, Joshua B. Tenenbaum, Antonio Torralba:
Learning to Learn with Compound HD Models. NIPS 2011: 2061-2069 - [c25]Rina Foygel, Ruslan Salakhutdinov, Ohad Shamir, Nati Srebro:
Learning with the weighted trace-norm under arbitrary sampling distributions. NIPS 2011: 2133-2141 - 2010
- [c24]Ruslan Salakhutdinov:
Learning Deep Boltzmann Machines using Adaptive MCMC. ICML 2010: 943-950 - [c23]Jason D. Lee, Ben Recht, Ruslan Salakhutdinov, Nathan Srebro, Joel A. Tropp:
Practical Large-Scale Optimization for Max-norm Regularization. NIPS 2010: 1297-1305 - [c22]Ruslan Salakhutdinov, Nathan Srebro:
Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm. NIPS 2010: 2056-2064 - [c21]Ruslan Salakhutdinov, Hugo Larochelle:
Efficient Learning of Deep Boltzmann Machines. AISTATS 2010: 693-700 - 2009
- [c20]Kai Yu, Ruslan Salakhutdinov, Yann LeCun, Geoffrey E. Hinton, Yoshua Bengio:
Workshop summary: Workshop on learning feature hierarchies. ICML 2009: 5 - [c19]John Langford, Ruslan Salakhutdinov, Tong Zhang:
Learning nonlinear dynamic models. ICML 2009: 593-600 - [c18]Hanna M. Wallach, Iain Murray, Ruslan Salakhutdinov, David M. Mimno:
Evaluation methods for topic models. ICML 2009: 1105-1112 - [c17]Ruslan Salakhutdinov:
Learning in Markov Random Fields using Tempered Transitions. NIPS 2009: 1598-1606 - [c16]Ruslan Salakhutdinov, Geoffrey E. Hinton:
Replicated Softmax: an Undirected Topic Model. NIPS 2009: 1607-1614 - [c15]Ilya Sutskever, Ruslan Salakhutdinov, Joshua B. Tenenbaum:
Modelling Relational Data using Bayesian Clustered Tensor Factorization. NIPS 2009: 1821-1828 - [c14]Ruslan Salakhutdinov, Geoffrey E. Hinton:
Deep Boltzmann Machines. AISTATS 2009: 448-455 - 2008
- [c13]Ruslan Salakhutdinov, Iain Murray:
On the quantitative analysis of deep belief networks. ICML 2008: 872-879 - [c12]Ruslan Salakhutdinov, Andriy Mnih:
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo. ICML 2008: 880-887 - [c11]Iain Murray, Ruslan Salakhutdinov:
Evaluating probabilities under high-dimensional latent variable models. NIPS 2008: 1137-1144 - 2007
- [c10]Ruslan Salakhutdinov, Andriy Mnih, Geoffrey E. Hinton:
Restricted Boltzmann machines for collaborative filtering. ICML 2007: 791-798 - [c9]Ruslan Salakhutdinov, Geoffrey E. Hinton:
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes. NIPS 2007: 1249-1256 - [c8]Ruslan Salakhutdinov, Andriy Mnih:
Probabilistic Matrix Factorization. NIPS 2007: 1257-1264 - [c7]Ruslan Salakhutdinov, Geoffrey E. Hinton:
Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure. AISTATS 2007: 412-419 - 2004
- [c6]Grigoris I. Karakoulas, Ruslan Salakhutdinov:
Semi-Supervised Mixture-of-Experts Classification. ICDM 2004: 138-145 - [c5]Jacob Goldberger, Sam T. Roweis, Geoffrey E. Hinton, Ruslan Salakhutdinov:
Neighbourhood Components Analysis. NIPS 2004: 513-520 - 2003
- [c4]Sam T. Roweis, Ruslan Salakhutdinov:
Simultaneous Localization and Surveying with Multiple Agents. European Summer School on Multi-AgentControl 2003: 313-332 - [c3]Ruslan Salakhutdinov, Sam T. Roweis:
Adaptive Overrelaxed Bound Optimization Methods. ICML 2003: 664-671 - [c2]Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani:
Optimization with EM and Expectation-Conjugate-Gradient. ICML 2003: 672-679 - [c1]Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani:
On the Convergence of Bound Optimization Algorithms. UAI 2003: 509-516
Editorship
- 2019
- [e1]Kamalika Chaudhuri, Ruslan Salakhutdinov:
Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA. Proceedings of Machine Learning Research 97, PMLR 2019 [contents]
Informal and Other Publications
- 2024
- [i221]Jing Yu Koh, Robert Lo, Lawrence Jang, Vikram Duvvur, Ming Chong Lim, Po-Yu Huang, Graham Neubig, Shuyan Zhou, Ruslan Salakhutdinov, Daniel Fried:
VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks. CoRR abs/2401.13649 (2024) - [i220]Raghav Kapoor, Yash Parag Butala, Melisa Russak, Jing Yu Koh, Kiran Kamble, Waseem AlShikh, Ruslan Salakhutdinov:
OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Web. CoRR abs/2402.17553 (2024) - [i219]Rohan Kumar, Youngmin Kim, Sunitha Ravi, Haitian Sun, Christos Faloutsos, Ruslan Salakhutdinov, Minji Yoon:
Automatic Question-Answer Generation for Long-Tail Knowledge. CoRR abs/2403.01382 (2024) - [i218]Benjamin Eysenbach, Vivek Myers, Ruslan Salakhutdinov, Sergey Levine:
Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference. CoRR abs/2403.04082 (2024) - [i217]Yutong He, Alexander Robey, Naoki Murata, Yiding Jiang, Joshua Williams, George J. Pappas, Hamed Hassani, Yuki Mitsufuji, Ruslan Salakhutdinov, J. Zico Kolter:
Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation. CoRR abs/2403.19103 (2024) - 2023
- [i216]Jing Yu Koh, Ruslan Salakhutdinov, Daniel Fried:
Grounding Language Models to Images for Multimodal Generation. CoRR abs/2301.13823 (2023) - [i215]Brandon Trabucco, Kyle Doherty, Max Gurinas, Ruslan Salakhutdinov:
Effective Data Augmentation With Diffusion Models. CoRR abs/2302.07944 (2023) - [i214]Paul Pu Liang, Yun Cheng, Xiang Fan, Chun Kai Ling, Suzanne Nie, Richard J. Chen, Zihao Deng, Faisal Mahmood, Ruslan Salakhutdinov, Louis-Philippe Morency:
Quantifying & Modeling Feature Interactions: An Information Decomposition Framework. CoRR abs/2302.12247 (2023) - [i213]Yue Wu, So Yeon Min, Yonatan Bisk, Ruslan Salakhutdinov, Amos Azaria, Yuanzhi Li, Tom M. Mitchell, Shrimai Prabhumoye:
Plan, Eliminate, and Track - Language Models are Good Teachers for Embodied Agents. CoRR abs/2305.02412 (2023) - [i212]Yue Wu, Shrimai Prabhumoye, So Yeon Min, Yonatan Bisk, Ruslan Salakhutdinov, Amos Azaria, Tom M. Mitchell, Yuanzhi Li:
SPRING: GPT-4 Out-performs RL Algorithms by Studying Papers and Reasoning. CoRR abs/2305.15486 (2023) - [i211]Murtaza Dalal, Ajay Mandlekar, Caelan Reed Garrett, Ankur Handa, Ruslan Salakhutdinov, Dieter Fox:
Imitating Task and Motion Planning with Visuomotor Transformers. CoRR abs/2305.16309 (2023) - [i210]Jing Yu Koh, Daniel Fried, Ruslan Salakhutdinov:
Generating Images with Multimodal Language Models. CoRR abs/2305.17216 (2023) - [i209]Chongyi Zheng, Benjamin Eysenbach, Homer Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine:
Stabilizing Contrastive RL: Techniques for Offline Goal Reaching. CoRR abs/2306.03346 (2023) - [i208]Paul Pu Liang, Yun Cheng, Ruslan Salakhutdinov, Louis-Philippe Morency:
Multimodal Fusion Interactions: A Study of Human and Automatic Quantification. CoRR abs/2306.04125 (2023) - [i207]Paul Pu Liang, Chun Kai Ling, Yun Cheng, Alex Obolenskiy, Yudong Liu, Rohan Pandey, Alex Wilf, Louis-Philippe Morency, Ruslan Salakhutdinov:
Multimodal Learning Without Labeled Multimodal Data: Guarantees and Applications. CoRR abs/2306.04539 (2023) - [i206]Paul Pu Liang, Zihao Deng, Martin Ma, James Zou, Louis-Philippe Morency, Ruslan Salakhutdinov:
Factorized Contrastive Learning: Going Beyond Multi-view Redundancy. CoRR abs/2306.05268 (2023) - [i205]Yutong He, Ruslan Salakhutdinov, J. Zico Kolter:
Localized Text-to-Image Generation for Free via Cross Attention Control. CoRR abs/2306.14636 (2023) - [i204]Paul Pu Liang, Yiwei Lyu, Xiang Fan, Arav Agarwal, Yun Cheng, Louis-Philippe Morency, Ruslan Salakhutdinov:
MultiZoo & MultiBench: A Standardized Toolkit for Multimodal Deep Learning. CoRR abs/2306.16413 (2023) - [i203]Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov:
A Connection between One-Step Regularization and Critic Regularization in Reinforcement Learning. CoRR abs/2307.12968 (2023) - [i202]Kyle Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn:
Contrastive Example-Based Control. CoRR abs/2307.13101 (2023) - [i201]Haitian Sun, William W. Cohen, Ruslan Salakhutdinov:
Answering Ambiguous Questions with a Database of Questions, Answers, and Revisions. CoRR abs/2308.08661 (2023) - [i200]Ted Moskovitz, Aaditya K. Singh, DJ Strouse, Tuomas Sandholm, Ruslan Salakhutdinov, Anca D. Dragan, Stephen McAleer:
Confronting Reward Model Overoptimization with Constrained RLHF. CoRR abs/2310.04373 (2023) - [i199]Minji Yoon, Jing Yu Koh, Bryan Hooi, Ruslan Salakhutdinov:
Multimodal Graph Learning for Generative Tasks. CoRR abs/2310.07478 (2023) - [i198]Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach:
Contrastive Difference Predictive Coding. CoRR abs/2310.20141 (2023) - [i197]Shentong Mo, Paul Pu Liang, Russ Salakhutdinov, Louis-Philippe Morency:
MultiIoT: Towards Large-scale Multisensory Learning for the Internet of Things. CoRR abs/2311.06217 (2023) - [i196]Haofei Yu, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency:
MMOE: Mixture of Multimodal Interaction Experts. CoRR abs/2311.09580 (2023) - [i195]Yutong He, Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Dongjun Kim, Wei-Hsiang Liao, Yuki Mitsufuji, J. Zico Kolter, Ruslan Salakhutdinov, Stefano Ermon:
Manifold Preserving Guided Diffusion. CoRR abs/2311.16424 (2023) - 2022
- [i194]Yao-Hung Hubert Tsai, Tianqin Li, Martin Q. Ma, Han Zhao, Kun Zhang, Louis-Philippe Morency, Ruslan Salakhutdinov:
Conditional Contrastive Learning with Kernel. CoRR abs/2202.05458 (2022) - [i193]Yao-Hung Hubert Tsai, Tianqin Li, Weixin Liu, Peiyuan Liao, Ruslan Salakhutdinov, Louis-Philippe Morency:
Learning Weakly-Supervised Contrastive Representations. CoRR abs/2202.06670 (2022) - [i192]Paul Pu Liang, Yiwei Lyu, Xiang Fan, Shentong Mo, Dani Yogatama, Louis-Philippe Morency, Ruslan Salakhutdinov:
HighMMT: Towards Modality and Task Generalization for High-Modality Representation Learning. CoRR abs/2203.01311 (2022) - [i191]Yiwei Lyu, Paul Pu Liang, Zihao Deng, Ruslan Salakhutdinov, Louis-Philippe Morency:
DIME: Fine-grained Interpretations of Multimodal Models via Disentangled Local Explanations. CoRR abs/2203.02013 (2022) - [i190]Minji Yoon, John Palowitch, Dustin Zelle, Ziniu Hu, Ruslan Salakhutdinov, Bryan Perozzi:
Zero-shot Domain Adaptation of Heterogeneous Graphs via Knowledge Transfer Networks. CoRR abs/2203.02018 (2022) - [i189]Samuel Yu, Peter Wu, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency:
PACS: A Dataset for Physical Audiovisual CommonSense Reasoning. CoRR abs/2203.11130 (2022) - [i188]Haitian Sun, William W. Cohen, Ruslan Salakhutdinov:
Reasoning over Logically Interacted Conditions for Question Answering. CoRR abs/2205.12898 (2022) - [i187]Benjamin Eysenbach, Soumith Udatha, Sergey Levine, Ruslan Salakhutdinov:
Imitating Past Successes can be Very Suboptimal. CoRR abs/2206.03378 (2022) - [i186]Benjamin Eysenbach, Tianjun Zhang, Ruslan Salakhutdinov, Sergey Levine:
Contrastive Learning as Goal-Conditioned Reinforcement Learning. CoRR abs/2206.07568 (2022) - [i185]Brandon Trabucco, Gunnar A. Sigurdsson, Robinson Piramuthu, Gaurav S. Sukhatme, Ruslan Salakhutdinov:
A Simple Approach for Visual Rearrangement: 3D Mapping and Semantic Search. CoRR abs/2206.13396 (2022) - [i184]Paul Pu Liang, Yiwei Lyu, Gunjan Chhablani, Nihal Jain, Zihao Deng, Xingbo Wang, Louis-Philippe Morency, Ruslan Salakhutdinov:
MultiViz: An Analysis Benchmark for Visualizing and Understanding Multimodal Models. CoRR abs/2207.00056 (2022) - [i183]Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Ruslan Salakhutdinov:
Scalable Privacy-enhanced Benchmark Graph Generative Model for Graph Convolutional Networks. CoRR abs/2207.04396 (2022) - [i182]Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Ruslan Salakhutdinov:
Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective. CoRR abs/2209.08466 (2022) - [i181]Cheng-Fu Yang, Yao-Hung Hubert Tsai, Wan-Cyuan Fan, Ruslan Salakhutdinov, Louis-Philippe Morency, Yu-Chiang Frank Wang:
Paraphrasing Is All You Need for Novel Object Captioning. CoRR abs/2209.12343 (2022) - [i180]So Yeon Min, Hao Zhu, Ruslan Salakhutdinov, Yonatan Bisk:
Don't Copy the Teacher: Data and Model Challenges in Embodied Dialogue. CoRR abs/2210.04443 (2022) - [i179]Yuxin Xiao, Paul Pu Liang, Umang Bhatt, Willie Neiswanger, Ruslan Salakhutdinov, Louis-Philippe Morency:
Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis. CoRR abs/2210.04714 (2022) - [i178]Xiang Fan, Yiwei Lyu, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency:
Nano: Nested Human-in-the-Loop Reward Learning for Few-shot Language Model Control. CoRR abs/2211.05750 (2022) - [i177]So Yeon Min, Yao-Hung Hubert Tsai, Wei Ding, Ali Farhadi, Ruslan Salakhutdinov, Yonatan Bisk, Jian Zhang:
Object Goal Navigation with End-to-End Self-Supervision. CoRR abs/2212.05923 (2022) - [i176]Rohan Pandey, Rulin Shao, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency:
Cross-modal Attention Congruence Regularization for Vision-Language Relation Alignment. CoRR abs/2212.10549 (2022) - 2021
- [i175]Peter Wu, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency:
Understanding the Tradeoffs in Client-Side Privacy for Speech Recognition. CoRR abs/2101.08919 (2021) - [i174]William H. Guss, Mario Ynocente Castro, Sam Devlin, Brandon Houghton, Noboru Sean Kuno, Crissman Loomis, Stephanie Milani, Sharada P. Mohanty, Keisuke Nakata, Ruslan Salakhutdinov, John Schulman, Shinya Shiroshita, Nicholay Topin, Avinash Ummadisingu, Oriol Vinyals:
The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors. CoRR abs/2101.11071 (2021) - [i173]Haitian Sun, Pat Verga, Bhuwan Dhingra, Ruslan Salakhutdinov, William W. Cohen:
Reasoning Over Virtual Knowledge Bases With Open Predicate Relations. CoRR abs/2102.07043 (2021) - [i172]Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, J. Zico Kolter, Sivaraman Balakrishnan, Zachary C. Lipton, Ruslan Salakhutdinov, Pradeep Ravikumar:
On Proximal Policy Optimization's Heavy-tailed Gradients. CoRR abs/2102.10264 (2021) - [i171]Ruosong Wang, Yifan Wu, Ruslan Salakhutdinov, Sham M. Kakade:
Instabilities of Offline RL with Pre-Trained Neural Representation. CoRR abs/2103.04947 (2021) - [i170]Yao-Hung Hubert Tsai, Martin Q. Ma, Muqiao Yang, Han Zhao, Louis-Philippe Morency, Ruslan Salakhutdinov:
Self-supervised Representation Learning with Relative Predictive Coding. CoRR abs/2103.11275 (2021) - [i169]Benjamin Eysenbach, Sergey Levine, Ruslan Salakhutdinov:
Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification. CoRR abs/2103.12656 (2021) - [i168]Emilio Parisotto, Ruslan Salakhutdinov:
Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation. CoRR abs/2104.01655 (2021) - [i167]Yiwei Lyu, Paul Pu Liang, Hai Pham, Eduard H. Hovy, Barnabás Póczos, Ruslan Salakhutdinov, Louis-Philippe Morency:
StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer. CoRR abs/2104.05196 (2021) - [i166]Shrimai Prabhumoye, Kazuma Hashimoto, Yingbo Zhou, Alan W. Black, Ruslan Salakhutdinov:
Focused Attention Improves Document-Grounded Generation. CoRR abs/2104.12714 (2021) - [i165]Yao-Hung Hubert Tsai, Shaojie Bai, Louis-Philippe Morency, Ruslan Salakhutdinov:
A Note on Connecting Barlow Twins with Negative-Sample-Free Contrastive Learning. CoRR abs/2104.13712 (2021) - [i164]Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh:
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning. CoRR abs/2105.08140 (2021) - [i163]Haitian Sun, William W. Cohen, Ruslan Salakhutdinov:
End-to-End Multihop Retrieval for Compositional Question Answering over Long Documents. CoRR abs/2106.00200 (2021) - [i162]Yao-Hung Hubert Tsai, Martin Q. Ma, Han Zhao, Kun Zhang, Louis-Philippe Morency, Ruslan Salakhutdinov:
Conditional Contrastive Learning: Removing Undesirable Information in Self-Supervised Representations. CoRR abs/2106.02866 (2021) - [i161]Yao-Hung Hubert Tsai, Tianqin Li, Weixin Liu, Peiyuan Liao, Ruslan Salakhutdinov, Louis-Philippe Morency:
Integrating Auxiliary Information in Self-supervised Learning. CoRR abs/2106.02869 (2021) - [i160]Dingwen Kong, Ruslan Salakhutdinov, Ruosong Wang, Lin F. Yang:
Online Sub-Sampling for Reinforcement Learning with General Function Approximation. CoRR abs/2106.07203 (2021) - [i159]Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, Kushal Lakhotia, Ruslan Salakhutdinov, Abdelrahman Mohamed:
HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units. CoRR abs/2106.07447 (2021) - [i158]Paul Pu Liang, Terrance Liu, Anna Cai, Michal Muszynski, Ryo Ishii, Nicholas B. Allen, Randy Auerbach, David Brent, Ruslan Salakhutdinov, Louis-Philippe Morency:
Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data. CoRR abs/2106.13213 (2021) - [i157]Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, Ruslan Salakhutdinov:
Towards Understanding and Mitigating Social Biases in Language Models. CoRR abs/2106.13219 (2021) - [i156]Paul Pu Liang, Yiwei Lyu, Xiang Fan, Zetian Wu, Yun Cheng, Jason Wu, Leslie Chen, Peter Wu, Michelle A. Lee, Yuke Zhu, Ruslan Salakhutdinov, Louis-Philippe Morency:
MultiBench: Multiscale Benchmarks for Multimodal Representation Learning. CoRR abs/2107.07502 (2021) - [i155]Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
Robust Predictable Control. CoRR abs/2109.03214 (2021) - [i154]Yanan Zheng, Jing Zhou, Yujie Qian, Ming Ding, Jian Li, Ruslan Salakhutdinov, Jie Tang, Sebastian Ruder, Zhilin Yang:
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding. CoRR abs/2109.12742 (2021) - [i153]Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
The Information Geometry of Unsupervised Reinforcement Learning. CoRR abs/2110.02719 (2021) - [i152]Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov:
Mismatched No More: Joint Model-Policy Optimization for Model-Based RL. CoRR abs/2110.02758 (2021) - [i151]Tianwei Ni, Benjamin Eysenbach, Ruslan Salakhutdinov:
Recurrent Model-Free RL is a Strong Baseline for Many POMDPs. CoRR abs/2110.05038 (2021) - [i150]Haitian Sun, William W. Cohen, Ruslan Salakhutdinov:
ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers. CoRR abs/2110.06884 (2021) - [i149]So Yeon Min, Devendra Singh Chaplot, Pradeep Ravikumar, Yonatan Bisk, Ruslan Salakhutdinov:
FILM: Following Instructions in Language with Modular Methods. CoRR abs/2110.07342 (2021) - [i148]Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez:
C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks. CoRR abs/2110.12080 (2021) - [i147]Murtaza Dalal, Deepak Pathak, Ruslan Salakhutdinov:
Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives. CoRR abs/2110.15360 (2021) - [i146]Devendra Singh Chaplot, Murtaza Dalal, Saurabh Gupta, Jitendra Malik, Ruslan Salakhutdinov:
SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency. CoRR abs/2112.01001 (2021) - 2020
- [i145]Paul Pu Liang, Terrance Liu, Ziyin Liu, Ruslan Salakhutdinov, Louis-Philippe Morency:
Think Locally, Act Globally: Federated Learning with Local and Global Representations. CoRR abs/2001.01523 (2020) - [i144]Yao-Hung Hubert Tsai, Nitish Srivastava, Hanlin Goh, Ruslan Salakhutdinov:
Capsules with Inverted Dot-Product Attention Routing. CoRR abs/2002.04764 (2020) - [i143]Ziyin Liu, Blair Chen, Ru Wang, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency, Masahito Ueda:
Learning Not to Learn in the Presence of Noisy Labels. CoRR abs/2002.06541 (2020) - [i142]Bhuwan Dhingra, Manzil Zaheer, Vidhisha Balachandran, Graham Neubig, Ruslan Salakhutdinov, William W. Cohen:
Differentiable Reasoning over a Virtual Knowledge Base. CoRR abs/2002.10640 (2020) - [i141]Benjamin Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov:
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement. CoRR abs/2002.11089 (2020) - [i140]Paul Pu Liang, Jeffrey Chen, Ruslan Salakhutdinov, Louis-Philippe Morency, Satwik Kottur:
On Emergent Communication in Competitive Multi-Agent Teams. CoRR abs/2003.01848 (2020) - [i139]Yao-Yuan Yang, Cyrus Rashtchian, Hongyang Zhang, Ruslan Salakhutdinov, Kamalika Chaudhuri:
Adversarial Robustness Through Local Lipschitzness. CoRR abs/2003.02460 (2020) - [i138]Lisa Lee, Benjamin Eysenbach, Ruslan Salakhutdinov, Shixiang Gu, Chelsea Finn:
Weakly-Supervised Reinforcement Learning for Controllable Behavior. CoRR abs/2004.02860 (2020) - [i137]Devendra Singh Chaplot, Dhiraj Gandhi, Saurabh Gupta, Abhinav Gupta, Ruslan Salakhutdinov:
Learning to Explore using Active Neural SLAM. CoRR abs/2004.05155 (2020) - [i136]Yao-Hung Hubert Tsai, Martin Q. Ma, Muqiao Yang, Ruslan Salakhutdinov, Louis-Philippe Morency:
Interpretable Multimodal Routing for Human Multimodal Language. CoRR abs/2004.14198 (2020) - [i135]Aman Madaan, Amrith Setlur, Tanmay Parekh, Barnabás Póczos, Graham Neubig, Yiming Yang, Ruslan Salakhutdinov, Alan W. Black, Shrimai Prabhumoye:
Politeness Transfer: A Tag and Generate Approach. CoRR abs/2004.14257 (2020) - [i134]Shrimai Prabhumoye, Ruslan Salakhutdinov, Alan W. Black:
Topological Sort for Sentence Ordering. CoRR abs/2005.00432 (2020) - [i133]Shrimai Prabhumoye, Alan W. Black, Ruslan Salakhutdinov:
Exploring Controllable Text Generation Techniques. CoRR abs/2005.01822 (2020) - [i132]Brandon Houghton, Stephanie Milani, Nicholay Topin, William H. Guss, Katja Hofmann, Diego Perez Liebana, Manuela Veloso, Ruslan Salakhutdinov:
Guaranteeing Reproducibility in Deep Learning Competitions. CoRR abs/2005.06041 (2020) - [i131]Ruosong Wang, Ruslan Salakhutdinov, Lin F. Yang:
Provably Efficient Reinforcement Learning with General Value Function Approximation. CoRR abs/2005.10804 (2020) - [i130]Mathis Petrovich, Chao Liang, Yanbin Liu, Yao-Hung Hubert Tsai, Linchao Zhu, Yi Yang, Ruslan Salakhutdinov, Makoto Yamada:
Feature Robust Optimal Transport for High-dimensional Data. CoRR abs/2005.12123 (2020) - [i129]Devendra Singh Chaplot, Ruslan Salakhutdinov, Abhinav Gupta, Saurabh Gupta:
Neural Topological SLAM for Visual Navigation. CoRR abs/2005.12256 (2020) - [i128]Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov:
Neural Methods for Point-wise Dependency Estimation. CoRR abs/2006.05553 (2020) - [i127]Yao-Hung Hubert Tsai, Yue Wu, Ruslan Salakhutdinov, Louis-Philippe Morency:
Demystifying Self-Supervised Learning: An Information-Theoretical Framework. CoRR abs/2006.05576 (2020) - [i126]Ruosong Wang, Simon S. Du, Lin F. Yang, Ruslan Salakhutdinov:
On Reward-Free Reinforcement Learning with Linear Function Approximation. CoRR abs/2006.11274 (2020) - [i125]Benjamin Eysenbach, Swapnil Asawa, Shreyas Chaudhari, Ruslan Salakhutdinov, Sergey Levine:
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers. CoRR abs/2006.13916 (2020) - [i124]Devendra Singh Chaplot, Dhiraj Gandhi, Abhinav Gupta, Ruslan Salakhutdinov:
Object Goal Navigation using Goal-Oriented Semantic Exploration. CoRR abs/2007.00643 (2020) - [i123]Paul Pu Liang, Irene Mengze Li, Emily Zheng, Yao Chong Lim, Ruslan Salakhutdinov, Louis-Philippe Morency:
Towards Debiasing Sentence Representations. CoRR abs/2007.08100 (2020) - [i122]Vivek Roy, Yan Xu, Yu-Xiong Wang, Kris Kitani, Ruslan Salakhutdinov, Martial Hebert:
Few-Shot Learning with Intra-Class Knowledge Transfer. CoRR abs/2008.09892 (2020) - [i121]Devendra Singh Sachan, Manzil Zaheer, Ruslan Salakhutdinov:
Revisiting LSTM Networks for Semi-Supervised Text Classification via Mixed Objective Function. CoRR abs/2009.04007 (2020) - [i120]Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi S. Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov:
Graph Adversarial Networks: Protecting Information against Adversarial Attacks. CoRR abs/2009.13504 (2020) - [i119]Shrimai Prabhumoye, Brendon Boldt, Ruslan Salakhutdinov, Alan W. Black:
Case Study: Deontological Ethics in NLP. CoRR abs/2010.04658 (2020) - [i118]Ruosong Wang, Hanrui Zhang, Devendra Singh Chaplot, Denis Garagic, Ruslan Salakhutdinov:
Planning with Submodular Objective Functions. CoRR abs/2010.11863 (2020) - [i117]Shangda Li, Devendra Singh Chaplot, Yao-Hung Hubert Tsai, Yue Wu, Louis-Philippe Morency, Ruslan Salakhutdinov:
Unsupervised Domain Adaptation for Visual Navigation. CoRR abs/2010.14543 (2020) - [i116]Yao-Yuan Yang, Cyrus Rashtchian, Ruslan Salakhutdinov, Kamalika Chaudhuri:
Close Category Generalization. CoRR abs/2011.08485 (2020) - [i115]Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
C-Learning: Learning to Achieve Goals via Recursive Classification. CoRR abs/2011.08909 (2020) - [i114]Paul Pu Liang, Peter Wu, Ziyin Liu, Louis-Philippe Morency, Ruslan Salakhutdinov:
Cross-Modal Generalization: Learning in Low Resource Modalities via Meta-Alignment. CoRR abs/2012.02813 (2020) - 2019
- [i113]Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc V. Le, Ruslan Salakhutdinov:
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context. CoRR abs/1901.02860 (2019) - [i112]Devendra Singh Chaplot, Lisa Lee, Ruslan Salakhutdinov, Devi Parikh, Dhruv Batra:
Embodied Multimodal Multitask Learning. CoRR abs/1902.01385 (2019) - [i111]Brenden M. Lake, Ruslan Salakhutdinov, Joshua B. Tenenbaum:
The Omniglot Challenge: A 3-Year Progress Report. CoRR abs/1902.03477 (2019) - [i110]Emilio Parisotto, Soham Ghosh, Sai Bhargav Yalamanchi, Varsha Chinnaobireddy, Yuhuai Wu, Ruslan Salakhutdinov:
Concurrent Meta Reinforcement Learning. CoRR abs/1903.02710 (2019) - [i109]Yao-Hung Hubert Tsai, Santosh Kumar Divvala, Louis-Philippe Morency, Ruslan Salakhutdinov, Ali Farhadi:
Video Relationship Reasoning using Gated Spatio-Temporal Energy Graph. CoRR abs/1903.10547 (2019) - [i108]William H. Guss, Cayden Codel, Katja Hofmann, Brandon Houghton, Noburu Kuno, Stephanie Milani, Sharada P. Mohanty, Diego Perez Liebana, Ruslan Salakhutdinov, Nicholay Topin, Manuela Veloso, Phillip Wang:
The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors. CoRR abs/1904.10079 (2019) - [i107]Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang:
On Exact Computation with an Infinitely Wide Neural Net. CoRR abs/1904.11955 (2019) - [i106]Simon S. Du, Kangcheng Hou, Barnabás Póczos, Ruslan Salakhutdinov, Ruosong Wang, Keyulu Xu:
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels. CoRR abs/1905.13192 (2019) - [i105]Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang, J. Zico Kolter, Louis-Philippe Morency, Ruslan Salakhutdinov:
Multimodal Transformer for Unaligned Multimodal Language Sequences. CoRR abs/1906.00295 (2019) - [i104]Paul Pu Liang, Yao Chong Lim, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov, Louis-Philippe Morency:
Strong and Simple Baselines for Multimodal Utterance Embeddings. CoRR abs/1906.02125 (2019) - [i103]Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning. CoRR abs/1906.05253 (2019) - [i102]Lisa Lee, Benjamin Eysenbach, Emilio Parisotto, Eric P. Xing, Sergey Levine, Ruslan Salakhutdinov:
Efficient Exploration via State Marginal Matching. CoRR abs/1906.05274 (2019) - [i101]Shrimai Prabhumoye, Khyathi Raghavi Chandu, Ruslan Salakhutdinov, Alan W. Black:
"My Way of Telling a Story": Persona based Grounded Story Generation. CoRR abs/1906.06401 (2019) - [i100]Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, Quoc V. Le:
XLNet: Generalized Autoregressive Pretraining for Language Understanding. CoRR abs/1906.08237 (2019) - [i99]Ziyin Liu, Zhikang Wang, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency, Masahito Ueda:
Deep Gamblers: Learning to Abstain with Portfolio Theory. CoRR abs/1907.00208 (2019) - [i98]Paul Pu Liang, Zhun Liu, Yao-Hung Hubert Tsai, Qibin Zhao, Ruslan Salakhutdinov, Louis-Philippe Morency:
Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization. CoRR abs/1907.01011 (2019) - [i97]Han Zhao, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov, Geoffrey J. Gordon:
Learning Neural Networks with Adaptive Regularization. CoRR abs/1907.06288 (2019) - [i96]William H. Guss, Brandon Houghton, Nicholay Topin, Phillip Wang, Cayden Codel, Manuela Veloso, Ruslan Salakhutdinov:
MineRL: A Large-Scale Dataset of Minecraft Demonstrations. CoRR abs/1907.13440 (2019) - [i95]Yao-Hung Hubert Tsai, Shaojie Bai, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov:
Transformer Dissection: An Unified Understanding for Transformer's Attention via the Lens of Kernel. CoRR abs/1908.11775 (2019) - [i94]Yanbin Liu, Makoto Yamada, Yao-Hung Hubert Tsai, Tam Le, Ruslan Salakhutdinov, Yi Yang:
LSMI-Sinkhorn: Semi-supervised Squared-Loss Mutual Information Estimation with Optimal Transport. CoRR abs/1909.02373 (2019) - [i93]William H. Guss, Ruslan Salakhutdinov:
On Universal Approximation by Neural Networks with Uniform Guarantees on Approximation of Infinite Dimensional Maps. CoRR abs/1910.01545 (2019) - [i92]Sanjeev Arora, Simon S. Du, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang, Dingli Yu:
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks. CoRR abs/1910.01663 (2019) - [i91]Muqiao Yang, Martin Q. Ma, Dongyu Li, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov:
Complex Transformer: A Framework for Modeling Complex-Valued Sequence. CoRR abs/1910.10202 (2019) - [i90]Zhiting Hu, Bowen Tan, Ruslan Salakhutdinov, Tom M. Mitchell, Eric P. Xing:
Learning Data Manipulation for Augmentation and Weighting. CoRR abs/1910.12795 (2019) - [i89]Zhiyuan Li, Ruosong Wang, Dingli Yu, Simon S. Du, Wei Hu, Ruslan Salakhutdinov, Sanjeev Arora:
Enhanced Convolutional Neural Tangent Kernels. CoRR abs/1911.00809 (2019) - [i88]Yichuan Charlie Tang, Ruslan Salakhutdinov:
Multiple Futures Prediction. CoRR abs/1911.00997 (2019) - [i87]Yichuan Charlie Tang, Jian Zhang, Ruslan Salakhutdinov:
Worst Cases Policy Gradients. CoRR abs/1911.03618 (2019) - [i86]Nitish Srivastava, Hanlin Goh, Ruslan Salakhutdinov:
Geometric Capsule Autoencoders for 3D Point Clouds. CoRR abs/1912.03310 (2019) - 2018
- [i85]Devendra Singh Chaplot, Ruslan Salakhutdinov:
Knowledge-based Word Sense Disambiguation using Topic Models. CoRR abs/1801.01900 (2018) - [i84]Devendra Singh Sachan, Manzil Zaheer, Ruslan Salakhutdinov:
Investigating the Working of Text Classifiers. CoRR abs/1801.06261 (2018) - [i83]Devendra Singh Chaplot, Emilio Parisotto, Ruslan Salakhutdinov:
Active Neural Localization. CoRR abs/1801.08214 (2018) - [i82]William H. Guss, Ruslan Salakhutdinov:
On Characterizing the Capacity of Neural Networks using Algebraic Topology. CoRR abs/1802.04443 (2018) - [i81]Denny Wu, Yixiu Zhao, Yao-Hung Hubert Tsai, Makoto Yamada, Ruslan Salakhutdinov:
"Dependency Bottleneck" in Auto-encoding Architectures: an Empirical Study. CoRR abs/1802.05408 (2018) - [i80]Yao-Hung Hubert Tsai, Makoto Yamada, Denny Wu, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu:
Selecting the Best in GANs Family: a Post Selection Inference Framework. CoRR abs/1802.05411 (2018) - [i79]Emilio Parisotto, Devendra Singh Chaplot, Jian Zhang, Ruslan Salakhutdinov:
Global Pose Estimation with an Attention-based Recurrent Network. CoRR abs/1802.06857 (2018) - [i78]Mario Srouji, Jian Zhang, Ruslan Salakhutdinov:
Structured Control Nets for Deep Reinforcement Learning. CoRR abs/1802.08311 (2018) - [i77]Bhuwan Dhingra, Qiao Jin, Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov:
Neural Models for Reasoning over Multiple Mentions using Coreference. CoRR abs/1804.05922 (2018) - [i76]Shrimai Prabhumoye, Yulia Tsvetkov, Ruslan Salakhutdinov, Alan W. Black:
Style Transfer Through Back-Translation. CoRR abs/1804.09000 (2018) - [i75]Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh:
How Many Samples are Needed to Learn a Convolutional Neural Network? CoRR abs/1805.07883 (2018) - [i74]Hongyang Zhang, Junru Shao, Ruslan Salakhutdinov:
Deep Neural Networks with Multi-Branch Architectures Are Less Non-Convex. CoRR abs/1806.01845 (2018) - [i73]Zhilin Yang, Junbo Jake Zhao, Bhuwan Dhingra, Kaiming He, William W. Cohen, Ruslan Salakhutdinov, Yann LeCun:
GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations. CoRR abs/1806.05662 (2018) - [i72]Yao-Hung Hubert Tsai, Paul Pu Liang, Amir Zadeh, Louis-Philippe Morency, Ruslan Salakhutdinov:
Learning Factorized Multimodal Representations. CoRR abs/1806.06176 (2018) - [i71]Lisa Lee, Emilio Parisotto, Devendra Singh Chaplot, Eric P. Xing, Ruslan Salakhutdinov:
Gated Path Planning Networks. CoRR abs/1806.06408 (2018) - [i70]Devendra Singh Chaplot, Christopher MacLellan, Ruslan Salakhutdinov, Kenneth R. Koedinger:
Learning Cognitive Models using Neural Networks. CoRR abs/1806.08065 (2018) - [i69]Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Xiaodan Liang, Lianhui Qin, Haoye Dong, Eric P. Xing:
Deep Generative Models with Learnable Knowledge Constraints. CoRR abs/1806.09764 (2018) - [i68]Haitian Sun, Bhuwan Dhingra, Manzil Zaheer, Kathryn Mazaitis, Ruslan Salakhutdinov, William W. Cohen:
Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text. CoRR abs/1809.00782 (2018) - [i67]Shrimai Prabhumoye, Yulia Tsvetkov, Alan W. Black, Ruslan Salakhutdinov:
Style Transfer Through Multilingual and Feedback-Based Back-Translation. CoRR abs/1809.06284 (2018) - [i66]Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, Christopher D. Manning:
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering. CoRR abs/1809.09600 (2018) - [i65]Haowen Xu, Hao Zhang, Zhiting Hu, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing:
AutoLoss: Learning Discrete Schedules for Alternate Optimization. CoRR abs/1810.02442 (2018) - [i64]Chun-Liang Li, Manzil Zaheer, Yang Zhang, Barnabás Póczos, Ruslan Salakhutdinov:
Point Cloud GAN. CoRR abs/1810.05795 (2018) - [i63]Maruan Al-Shedivat, Lisa Lee, Ruslan Salakhutdinov, Eric P. Xing:
On the Complexity of Exploration in Goal-Driven Navigation. CoRR abs/1811.06889 (2018) - [i62]Hongyang Zhang, Susu Xu, Jiantao Jiao, Pengtao Xie, Ruslan Salakhutdinov, Eric P. Xing:
Stackelberg GAN: Towards Provable Minimax Equilibrium via Multi-Generator Architectures. CoRR abs/1811.08010 (2018) - [i61]Bowen Tan, Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing:
Connecting the Dots Between MLE and RL for Sequence Generation. CoRR abs/1811.09740 (2018) - 2017
- [i60]Zhilin Yang, Junjie Hu, Ruslan Salakhutdinov, William W. Cohen:
Semi-Supervised QA with Generative Domain-Adaptive Nets. CoRR abs/1702.02206 (2017) - [i59]Zichao Yang, Zhiting Hu, Ruslan Salakhutdinov, Taylor Berg-Kirkpatrick:
Improved Variational Autoencoders for Text Modeling using Dilated Convolutions. CoRR abs/1702.08139 (2017) - [i58]Emilio Parisotto, Ruslan Salakhutdinov:
Neural Map: Structured Memory for Deep Reinforcement Learning. CoRR abs/1702.08360 (2017) - [i57]Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing:
Controllable Text Generation. CoRR abs/1703.00955 (2017) - [i56]Bhuwan Dhingra, Hanxiao Liu, Ruslan Salakhutdinov, William W. Cohen:
A Comparative Study of Word Embeddings for Reading Comprehension. CoRR abs/1703.00993 (2017) - [i55]Bhuwan Dhingra, Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov:
Linguistic Knowledge as Memory for Recurrent Neural Networks. CoRR abs/1703.02620 (2017) - [i54]Yao-Hung Hubert Tsai, Liang-Kang Huang, Ruslan Salakhutdinov:
Learning Robust Visual-Semantic Embeddings. CoRR abs/1703.05908 (2017) - [i53]Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabás Póczos, Ruslan Salakhutdinov, Alexander J. Smola:
Deep Sets. CoRR abs/1703.06114 (2017) - [i52]Zhilin Yang, Ruslan Salakhutdinov, William W. Cohen:
Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks. CoRR abs/1703.06345 (2017) - [i51]Yusuke Watanabe, Bhuwan Dhingra, Ruslan Salakhutdinov:
Question Answering from Unstructured Text by Retrieval and Comprehension. CoRR abs/1703.08885 (2017) - [i50]Behnam Neyshabur, Ryota Tomioka, Ruslan Salakhutdinov, Nathan Srebro:
Geometry of Optimization and Implicit Regularization in Deep Learning. CoRR abs/1705.03071 (2017) - [i49]Zihang Dai, Zhilin Yang, Fan Yang, William W. Cohen, Ruslan Salakhutdinov:
Good Semi-supervised Learning that Requires a Bad GAN. CoRR abs/1705.09783 (2017) - [i48]Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing:
On Unifying Deep Generative Models. CoRR abs/1706.00550 (2017) - [i47]Devendra Singh Chaplot, Kanthashree Mysore Sathyendra, Rama Kumar Pasumarthi, Dheeraj Rajagopal, Ruslan Salakhutdinov:
Gated-Attention Architectures for Task-Oriented Language Grounding. CoRR abs/1706.07230 (2017) - [i46]Adams Wei Yu, Qihang Lin, Ruslan Salakhutdinov, Jaime G. Carbonell:
Normalized Gradient with Adaptive Stepsize Method for Deep Neural Network Training. CoRR abs/1707.04822 (2017) - [i45]Sashank J. Reddi, Manzil Zaheer, Suvrit Sra, Barnabás Póczos, Francis R. Bach, Ruslan Salakhutdinov, Alexander J. Smola:
A Generic Approach for Escaping Saddle points. CoRR abs/1709.01434 (2017) - [i44]Yao-Hung Hubert Tsai, Ruslan Salakhutdinov:
Improving One-Shot Learning through Fusing Side Information. CoRR abs/1710.08347 (2017) - [i43]Yao-Hung Hubert Tsai, Han Zhao, Ruslan Salakhutdinov, Nebojsa Jojic:
Discovering Order in Unordered Datasets: Generative Markov Networks. CoRR abs/1711.03167 (2017) - [i42]Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov, William W. Cohen:
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model. CoRR abs/1711.03953 (2017) - 2016
- [i41]Saizheng Zhang, Yuhuai Wu, Tong Che, Zhouhan Lin, Roland Memisevic, Ruslan Salakhutdinov, Yoshua Bengio:
Architectural Complexity Measures of Recurrent Neural Networks. CoRR abs/1602.08210 (2016) - [i40]Zhilin Yang, Ruslan Salakhutdinov, William W. Cohen:
Multi-Task Cross-Lingual Sequence Tagging from Scratch. CoRR abs/1603.06270 (2016) - [i39]Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov:
Revisiting Semi-Supervised Learning with Graph Embeddings. CoRR abs/1603.08861 (2016) - [i38]Behnam Neyshabur, Yuhuai Wu, Ruslan Salakhutdinov, Nathan Srebro:
Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations. CoRR abs/1605.07154 (2016) - [i37]Zhilin Yang, Ye Yuan, Yuexin Wu, Ruslan Salakhutdinov, William W. Cohen:
Encode, Review, and Decode: Reviewer Module for Caption Generation. CoRR abs/1605.07912 (2016) - [i36]Bhuwan Dhingra, Hanxiao Liu, William W. Cohen, Ruslan Salakhutdinov:
Gated-Attention Readers for Text Comprehension. CoRR abs/1606.01549 (2016) - [i35]Yuhuai Wu, Saizheng Zhang, Ying Zhang, Yoshua Bengio, Ruslan Salakhutdinov:
On Multiplicative Integration with Recurrent Neural Networks. CoRR abs/1606.06630 (2016) - [i34]Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing:
Stochastic Variational Deep Kernel Learning. CoRR abs/1611.00336 (2016) - [i33]Zhilin Yang, Bhuwan Dhingra, Ye Yuan, Junjie Hu, William W. Cohen, Ruslan Salakhutdinov:
Words or Characters? Fine-grained Gating for Reading Comprehension. CoRR abs/1611.01724 (2016) - [i32]Yuhuai Wu, Yuri Burda, Ruslan Salakhutdinov, Roger B. Grosse:
On the Quantitative Analysis of Decoder-Based Generative Models. CoRR abs/1611.04273 (2016) - [i31]Michael Figurnov, Maxwell D. Collins, Yukun Zhu, Li Zhang, Jonathan Huang, Dmitry P. Vetrov, Ruslan Salakhutdinov:
Spatially Adaptive Computation Time for Residual Networks. CoRR abs/1612.02297 (2016) - [i30]Kenneth Marino, Ruslan Salakhutdinov, Abhinav Gupta:
The More You Know: Using Knowledge Graphs for Image Classification. CoRR abs/1612.04844 (2016) - 2015
- [i29]Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C. Courville, Ruslan Salakhutdinov, Richard S. Zemel, Yoshua Bengio:
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. CoRR abs/1502.03044 (2015) - [i28]Yukun Zhu, Raquel Urtasun, Ruslan Salakhutdinov, Sanja Fidler:
segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection. CoRR abs/1502.04275 (2015) - [i27]Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov:
Unsupervised Learning of Video Representations using LSTMs. CoRR abs/1502.04681 (2015) - [i26]Shengxin Zha, Florian Luisier, Walter Andrews, Nitish Srivastava, Ruslan Salakhutdinov:
Exploiting Image-trained CNN Architectures for Unconstrained Video Classification. CoRR abs/1503.04144 (2015) - [i25]Elman Mansimov, Nitish Srivastava, Ruslan Salakhutdinov:
Initialization Strategies of Spatio-Temporal Convolutional Neural Networks. CoRR abs/1503.07274 (2015) - [i24]Jimmy Ba, Kevin Swersky, Sanja Fidler, Ruslan Salakhutdinov:
Predicting Deep Zero-Shot Convolutional Neural Networks using Textual Descriptions. CoRR abs/1506.00511 (2015) - [i23]Behnam Neyshabur, Ruslan Salakhutdinov, Nathan Srebro:
Path-SGD: Path-Normalized Optimization in Deep Neural Networks. CoRR abs/1506.02617 (2015) - [i22]Yukun Zhu, Ryan Kiros, Richard S. Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, Sanja Fidler:
Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books. CoRR abs/1506.06724 (2015) - [i21]Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov, Richard S. Zemel, Antonio Torralba, Raquel Urtasun, Sanja Fidler:
Skip-Thought Vectors. CoRR abs/1506.06726 (2015) - [i20]Jimmy Ba, Roger B. Grosse, Ruslan Salakhutdinov, Brendan J. Frey:
Learning Wake-Sleep Recurrent Attention Models. CoRR abs/1509.06812 (2015) - [i19]Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing:
Deep Kernel Learning. CoRR abs/1511.02222 (2015) - [i18]Shikhar Sharma, Ryan Kiros, Ruslan Salakhutdinov:
Action Recognition using Visual Attention. CoRR abs/1511.04119 (2015) - [i17]R. Devon Hjelm, Kyunghyun Cho, Junyoung Chung, Ruslan Salakhutdinov, Vince D. Calhoun, Nebojsa Jojic:
Iterative Refinement of Approximate Posterior for Training Directed Belief Networks. CoRR abs/1511.06382 (2015) - 2014
- [i16]George E. Dahl, Navdeep Jaitly, Ruslan Salakhutdinov:
Multi-task Neural Networks for QSAR Predictions. CoRR abs/1406.1231 (2014) - [i15]Ryan Kiros, Richard S. Zemel, Ruslan Salakhutdinov:
A Multiplicative Model for Learning Distributed Text-Based Attribute Representations. CoRR abs/1406.2710 (2014) - [i14]Ryan Kiros, Ruslan Salakhutdinov, Richard S. Zemel:
Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models. CoRR abs/1411.2539 (2014) - [i13]Yuri Burda, Roger B. Grosse, Ruslan Salakhutdinov:
Accurate and Conservative Estimates of MRF Log-likelihood using Reverse Annealing. CoRR abs/1412.8566 (2014) - 2013
- [i12]Nitish Srivastava, Ruslan Salakhutdinov, Geoffrey E. Hinton:
Modeling Documents with Deep Boltzmann Machines. CoRR abs/1309.6865 (2013) - [i11]Behnam Neyshabur, Payman Yadollahpour, Yury Makarychev, Ruslan Salakhutdinov, Nathan Srebro:
The Power of Asymmetry in Binary Hashing. CoRR abs/1311.7662 (2013) - [i10]Yichuan Tang, Nitish Srivastava, Ruslan Salakhutdinov:
Learning generative models with visual attention. CoRR abs/1312.6110 (2013) - 2012
- [i9]Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton:
Deep Mixtures of Factor Analysers. CoRR abs/1206.4635 (2012) - [i8]Geoffrey E. Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, Ruslan Salakhutdinov:
Improving neural networks by preventing co-adaptation of feature detectors. CoRR abs/1207.0580 (2012) - [i7]Roger B. Grosse, Ruslan Salakhutdinov, William T. Freeman, Joshua B. Tenenbaum:
Exploiting compositionality to explore a large space of model structures. CoRR abs/1210.4856 (2012) - [i6]Rina Foygel, Nathan Srebro, Ruslan Salakhutdinov:
Matrix reconstruction with the local max norm. CoRR abs/1210.5196 (2012) - [i5]Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahramani:
On the Convergence of Bound Optimization Algorithms. CoRR abs/1212.2490 (2012) - 2011
- [i4]Dean P. Foster, Sham M. Kakade, Ruslan Salakhutdinov:
Domain Adaptation: Overfitting and Small Sample Statistics. CoRR abs/1105.0857 (2011) - [i3]Rina Foygel, Ruslan Salakhutdinov, Ohad Shamir, Nathan Srebro:
Learning with the Weighted Trace-norm under Arbitrary Sampling Distributions. CoRR abs/1106.4251 (2011) - 2010
- [i2]Ruslan Salakhutdinov, Nathan Srebro:
Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm. CoRR abs/1002.2780 (2010) - 2009
- [i1]John Langford, Ruslan Salakhutdinov, Tong Zhang:
Learning Nonlinear Dynamic Models. CoRR abs/0905.3369 (2009)
Coauthor Index
Benjamin Eysenbach
aka: Ben Eysenbach
aka: Ben Eysenbach
[j12] [c225] [c224] [c223] [c220] [c217] [c210] [c209] [c205] [c204] [c203] [c188] [c187] [c177] [c171] [c170] [c163] [c159] [c158] [c139] [c137] [c130] [c125] [c121] [i214] [i208] [i207] [i206] [i204] [i197] [i196] [i192] [i191] [i189] [i184] [i179] [i178] [i176] [i175] [i167] [i158] [i157] [i156] [i145] [i143] [i140] [i123] [i114] [i105] [i104] [i99] [i98] [i72]
[j12] [c225] [c224] [c223] [c220] [c217] [c210] [c209] [c205] [c204] [c203] [c199] [c198] [c192] [c188] [c187] [c181] [c180] [c177] [c171] [c170] [c163] [c159] [c158] [c155] [c145] [c139] [c137] [c134] [c133] [c130] [c125] [c121] [i214] [i208] [i207] [i206] [i204] [i197] [i196] [i194] [i193] [i192] [i191] [i189] [i184] [i181] [i179] [i178] [i176] [i175] [i170] [i167] [i165] [i162] [i161] [i158] [i157] [i156] [i145] [i143] [i140] [i136] [i128] [i127] [i123] [i117] [i114] [i109] [i105] [i104] [i99] [i98] [i95] [i72]
Nathan Srebro
aka: Nati Srebro
aka: Nati Srebro
Yichuan Tang
aka: Yichuan Charlie Tang
aka: Yichuan Charlie Tang
Yao-Hung Tsai
aka: Yao-Hung Hubert Tsai
aka: Yao-Hung Hubert Tsai
[j10] [c213] [c199] [c198] [c192] [c190] [c186] [c181] [c180] [c162] [c155] [c154] [c150] [c145] [c139] [c137] [c134] [c133] [c130] [c128] [c125] [c120] [c102] [c87] [i194] [i193] [i181] [i177] [i170] [i165] [i162] [i161] [i159] [i144] [i136] [i130] [i128] [i127] [i117] [i109] [i105] [i104] [i98] [i97] [i95] [i94] [i91] [i81] [i80] [i72] [i54] [i44] [i43]
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