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Kilian Q. Weinberger
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- affiliation: Department of Computer Science and Engineering, Washington University in St. Louis
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2020 – today
- 2024
- [j12]Zhenzhen Liu, Jin Peng Zhou, Kilian Q. Weinberger:
Leveraging diffusion models for unsupervised out-of-distribution detection on image manifold. Frontiers Artif. Intell. 7 (2024) - [c122]Justin Lovelace, Varsha Kishore, Yiwei Chen, Kilian Q. Weinberger:
Diffusion Guided Language Modeling. ACL (Findings) 2024: 14936-14952 - [c121]Tai-Yu Pan, Chenyang Ma, Tianle Chen, Cheng Perng Phoo, Katie Z. Luo, Yurong You, Mark Campbell, Kilian Q. Weinberger, Bharath Hariharan, Wei-Lun Chao:
Pre-training LiDAR-based 3D Object Detectors through Colorization. ICLR 2024 - [c120]Jin Peng Zhou, Charles Staats, Wenda Li, Christian Szegedy, Kilian Q. Weinberger, Yuhuai Wu:
Don't Trust: Verify - Grounding LLM Quantitative Reasoning with Autoformalization. ICLR 2024 - [c119]Katie Z. Luo, Xinshuo Weng, Yan Wang, Shuang Wu, Jie Li, Kilian Q. Weinberger, Yue Wang, Marco Pavone:
Augmenting Lane Perception and Topology Understanding with Standard Definition Navigation Maps. ICRA 2024: 4029-4035 - [c118]Yurong You, Cheng Perng Phoo, Carlos Andres Diaz-Ruiz, Katie Z. Luo, Wei-Lun Chao, Mark E. Campbell, Bharath Hariharan, Kilian Q. Weinberger:
Better Monocular 3D Detectors with LiDAR from the Past. ICRA 2024: 6634-6641 - [i97]Jiawei Yang, Katie Z. Luo, Jiefeng Li, Kilian Q. Weinberger, Yonglong Tian, Yue Wang:
Denoising Vision Transformers. CoRR abs/2401.02957 (2024) - [i96]Quang-Huy Nguyen, Jin Peng Zhou, Zhenzhen Liu, Khanh-Huyen Bui, Kilian Q. Weinberger, Dung D. Le
:
Zero-shot Object-Level OOD Detection with Context-Aware Inpainting. CoRR abs/2402.03292 (2024) - [i95]Ruihan Wu, Siddhartha Datta, Yi Su, Dheeraj Baby, Yu-Xiang Wang, Kilian Q. Weinberger:
Online Feature Updates Improve Online (Generalized) Label Shift Adaptation. CoRR abs/2402.03545 (2024) - [i94]Jin Peng Zhou, Charles Staats, Wenda Li, Christian Szegedy, Kilian Q. Weinberger, Yuhuai Wu:
Don't Trust: Verify - Grounding LLM Quantitative Reasoning with Autoformalization. CoRR abs/2403.18120 (2024) - [i93]Yurong You, Cheng Perng Phoo, Carlos Andres Diaz-Ruiz, Katie Z. Luo, Wei-Lun Chao, Mark E. Campbell, Bharath Hariharan, Kilian Q. Weinberger:
Better Monocular 3D Detectors with LiDAR from the Past. CoRR abs/2404.05139 (2024) - [i92]Xiangyu Chen, Zhenzhen Liu, Katie Z. Luo, Siddhartha Datta, Adhitya Polavaram, Yan Wang, Yurong You, Boyi Li, Marco Pavone, Wei-Lun Chao, Mark E. Campbell, Bharath Hariharan, Kilian Q. Weinberger:
DiffuBox: Refining 3D Object Detection with Point Diffusion. CoRR abs/2405.16034 (2024) - [i91]Jin Peng Zhou, Katie Z. Luo, Jingwen Gu, Jason Yuan, Kilian Q. Weinberger, Wen Sun:
Orchestrating LLMs with Different Personalizations. CoRR abs/2407.04181 (2024) - [i90]Jin Peng Zhou, Christian K. Belardi, Ruihan Wu, Travis Zhang, Carla P. Gomes, Wen Sun, Kilian Q. Weinberger:
On Speeding Up Language Model Evaluation. CoRR abs/2407.06172 (2024) - 2023
- [c117]Ruihan Wu, Jin Peng Zhou, Kilian Q. Weinberger, Chuan Guo:
Does Label Differential Privacy Prevent Label Inference Attacks? AISTATS 2023: 4336-4347 - [c116]Felix Wu, Kwangyoun Kim, Shinji Watanabe, Kyu Jeong Han, Ryan McDonald, Kilian Q. Weinberger, Yoav Artzi:
Wav2Seq: Pre-Training Speech-to-Text Encoder-Decoder Models Using Pseudo Languages. ICASSP 2023: 1-5 - [c115]Travis Zhang, Katie Luo, Cheng Perng Phoo, Yurong You, Wei-Lun Chao, Bharath Hariharan, Mark E. Campbell
, Kilian Q. Weinberger:
Unsupervised Domain Adaptation for Self-Driving from Past Traversal Features. ICCV (Workshops) 2023: 4042-4048 - [c114]Xiangyu Chen, Varsha Kishore, Kilian Q. Weinberger:
Learning Iterative Neural Optimizers for Image Steganography. ICLR 2023 - [c113]Varsha Kishore, Chao Wan, Justin Lovelace, Yoav Artzi, Kilian Q. Weinberger:
IncDSI: Incrementally Updatable Document Retrieval. ICML 2023: 17122-17134 - [c112]Zhenzhen Liu, Jin Peng Zhou, Yufan Wang, Kilian Q. Weinberger:
Unsupervised Out-of-Distribution Detection with Diffusion Inpainting. ICML 2023: 22528-22538 - [c111]Paloma Sodhi, Felix Wu, Ethan R. Elenberg, Kilian Q. Weinberger, Ryan McDonald:
On the Effectiveness of Offline RL for Dialogue Response Generation. ICML 2023: 32088-32104 - [c110]Youya Xia, Josephine Monica, Wei-Lun Chao, Bharath Hariharan, Kilian Q. Weinberger, Mark E. Campbell
:
Image-to-Image Translation for Autonomous Driving from Coarsely-Aligned Image Pairs. ICRA 2023: 7756-7762 - [c109]Justin Lovelace, Varsha Kishore, Chao Wan, Eliot Shekhtman, Kilian Q. Weinberger:
Latent Diffusion for Language Generation. NeurIPS 2023 - [c108]Katie Luo, Zhenzhen Liu, Xiangyu Chen, Yurong You, Sagie Benaim, Cheng Perng Phoo, Mark E. Campbell, Wen Sun, Bharath Hariharan, Kilian Q. Weinberger:
Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery. NeurIPS 2023 - [c107]Ruihan Wu, Xiangyu Chen, Chuan Guo, Kilian Q. Weinberger:
Learning To Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning. UAI 2023: 2293-2303 - [i89]Zhenzhen Liu, Jin Peng Zhou, Yufan Wang, Kilian Q. Weinberger:
Unsupervised Out-of-Distribution Detection with Diffusion Inpainting. CoRR abs/2302.10326 (2023) - [i88]Yurong You, Cheng Perng Phoo, Katie Z. Luo, Travis Zhang, Wei-Lun Chao, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Unsupervised Adaptation from Repeated Traversals for Autonomous Driving. CoRR abs/2303.15286 (2023) - [i87]Xiangyu Chen, Varsha Kishore, Kilian Q. Weinberger:
Learning Iterative Neural Optimizers for Image Steganography. CoRR abs/2303.16206 (2023) - [i86]Varsha Kishore, Chao Wan, Justin Lovelace, Yoav Artzi, Kilian Q. Weinberger:
IncDSI: Incrementally Updatable Document Retrieval. CoRR abs/2307.10323 (2023) - [i85]Paloma Sodhi, Felix Wu, Ethan R. Elenberg, Kilian Q. Weinberger, Ryan McDonald:
On the Effectiveness of Offline RL for Dialogue Response Generation. CoRR abs/2307.12425 (2023) - [i84]Travis Zhang, Katie Luo, Cheng Perng Phoo, Yurong You, Wei-Lun Chao, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Unsupervised Domain Adaptation for Self-Driving from Past Traversal Features. CoRR abs/2309.12140 (2023) - [i83]Tai-Yu Pan, Chenyang Ma, Tianle Chen, Cheng Perng Phoo, Katie Z. Luo, Yurong You, Mark E. Campbell, Kilian Q. Weinberger, Bharath Hariharan, Wei-Lun Chao:
Pre-Training LiDAR-Based 3D Object Detectors Through Colorization. CoRR abs/2310.14592 (2023) - [i82]Zhenzhen Liu, Chao Wan, Varsha Kishore, Jin Peng Zhou, Minmin Chen, Kilian Q. Weinberger:
Correction with Backtracking Reduces Hallucination in Summarization. CoRR abs/2310.16176 (2023) - [i81]Katie Z. Luo, Zhenzhen Liu, Xiangyu Chen, Yurong You, Sagie Benaim, Cheng Perng Phoo, Mark E. Campbell, Wen Sun, Bharath Hariharan, Kilian Q. Weinberger:
Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery. CoRR abs/2310.19080 (2023) - [i80]Katie Z. Luo, Xinshuo Weng, Yan Wang, Shuang Wu, Jie Li, Kilian Q. Weinberger, Yue Wang, Marco Pavone:
Augmenting Lane Perception and Topology Understanding with Standard Definition Navigation Maps. CoRR abs/2311.04079 (2023) - 2022
- [j11]Gao Huang
, Zhuang Liu
, Geoff Pleiss, Laurens van der Maaten, Kilian Q. Weinberger:
Convolutional Networks with Dense Connectivity. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 8704-8716 (2022) - [c106]Yurong You
, Katie Luo, Cheng Perng Phoo, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Learning to Detect Mobile Objects from LiDAR Scans Without Labels. CVPR 2022: 1120-1130 - [c105]Carlos Andres Diaz-Ruiz, Youya Xia, Yurong You
, Jose Nino, Junan Chen, Josephine Monica, Xiangyu Chen, Katie Luo, Yan Wang, Marc Emond, Wei-Lun Chao, Bharath Hariharan, Kilian Q. Weinberger, Mark E. Campbell:
Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions. CVPR 2022: 21351-21360 - [c104]Felix Wu, Kwangyoun Kim, Jing Pan, Kyu Jeong Han, Kilian Q. Weinberger, Yoav Artzi:
Performance-Efficiency Trade-Offs in Unsupervised Pre-Training for Speech Recognition. ICASSP 2022: 7667-7671 - [c103]Johan Bjorck, Carla P. Gomes, Kilian Q. Weinberger:
Is High Variance Unavoidable in RL? A Case Study in Continuous Control. ICLR 2022 - [c102]Varsha Kishore, Xiangyu Chen, Yan Wang, Boyi Li, Kilian Q. Weinberger:
Fixed Neural Network Steganography: Train the images, not the network. ICLR 2022 - [c101]Boyi Li, Kilian Q. Weinberger, Serge J. Belongie, Vladlen Koltun, René Ranftl:
Language-driven Semantic Segmentation. ICLR 2022 - [c100]Yurong You, Katie Z. Luo, Xiangyu Chen, Junan Chen, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception. ICLR 2022 - [c99]Yurong You
, Carlos Andres Diaz-Ruiz, Yan Wang, Wei-Lun Chao, Bharath Hariharan, Mark E. Campbell
, Kilian Q. Weinberger:
Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection in Self-Driving Cars. ICRA 2022: 5070-5077 - [c98]Ramya Ramakrishnan, Hashan Buddhika Narangodage, Mauro Schilman, Kilian Q. Weinberger, Ryan McDonald:
Long-term Control for Dialogue Generation: Methods and Evaluation. NAACL-HLT 2022: 738-753 - [c97]Yurong You, Cheng Perng Phoo, Katie Luo, Travis Zhang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger:
Unsupervised Adaptation from Repeated Traversals for Autonomous Driving. NeurIPS 2022 - [c96]Ruihan Wu, Xin Yang, Yuanshun Yao, Jiankai Sun, Tianyi Liu, Kilian Q. Weinberger, Chong Wang:
Differentially private multi-party data release for linear regression. UAI 2022: 2128-2137 - [i79]Boyi Li, Kilian Q. Weinberger, Serge J. Belongie, Vladlen Koltun, René Ranftl:
Language-driven Semantic Segmentation. CoRR abs/2201.03546 (2022) - [i78]Ruihan Wu, Jin Peng Zhou, Kilian Q. Weinberger, Chuan Guo:
Does Label Differential Privacy Prevent Label Inference Attacks? CoRR abs/2202.12968 (2022) - [i77]Yurong You, Katie Z. Luo, Xiangyu Chen, Junan Chen, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception. CoRR abs/2203.11405 (2022) - [i76]Yurong You, Katie Z. Luo, Cheng Perng Phoo, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Learning to Detect Mobile Objects from LiDAR Scans Without Labels. CoRR abs/2203.15882 (2022) - [i75]Felix Wu, Kwangyoun Kim, Shinji Watanabe, Kyu Jeong Han, Ryan McDonald, Kilian Q. Weinberger, Yoav Artzi:
Wav2Seq: Pre-training Speech-to-Text Encoder-Decoder Models Using Pseudo Languages. CoRR abs/2205.01086 (2022) - [i74]Ramya Ramakrishnan, Hashan Buddhika Narangodage, Mauro Schilman, Kilian Q. Weinberger, Ryan McDonald:
Long-term Control for Dialogue Generation: Methods and Evaluation. CoRR abs/2205.07352 (2022) - [i73]Ruihan Wu, Xin Yang, Yuanshun Yao, Jiankai Sun, Tianyi Liu, Kilian Q. Weinberger, Chong Wang:
Differentially Private Multi-Party Data Release for Linear Regression. CoRR abs/2206.07998 (2022) - [i72]Carlos Andres Diaz-Ruiz, Youya Xia, Yurong You
, Jose Nino, Junan Chen, Josephine Monica, Xiangyu Chen, Katie Luo, Yan Wang, Marc Emond, Wei-Lun Chao, Bharath Hariharan, Kilian Q. Weinberger, Mark Campbell:
Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions. CoRR abs/2208.01166 (2022) - [i71]Youya Xia, Josephine Monica, Wei-Lun Chao, Bharath Hariharan, Kilian Q. Weinberger, Mark Campbell:
Image-to-Image Translation for Autonomous Driving from Coarsely-Aligned Image Pairs. CoRR abs/2209.11673 (2022) - [i70]Ruihan Wu, Xiangyu Chen, Chuan Guo, Kilian Q. Weinberger:
Learning to Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning. CoRR abs/2210.10880 (2022) - [i69]Justin Lovelace, Varsha Kishore, Chao Wan, Eliot Shekhtman, Kilian Q. Weinberger:
Latent Diffusion for Language Generation. CoRR abs/2212.09462 (2022) - [i68]Boyi Li, Rodolfo Corona, Karttikeya Mangalam, Catherine Chen, Daniel Flaherty, Serge J. Belongie, Kilian Q. Weinberger, Jitendra Malik, Trevor Darrell, Dan Klein:
Does unsupervised grammar induction need pixels? CoRR abs/2212.10564 (2022) - 2021
- [c95]Johan Bjorck, Anmol Kabra, Kilian Q. Weinberger, Carla P. Gomes:
Characterizing the Loss Landscape in Non-Negative Matrix Factorization. AAAI 2021: 6768-6776 - [c94]Johan Bjorck, Kilian Q. Weinberger, Carla P. Gomes:
Understanding Decoupled and Early Weight Decay. AAAI 2021: 6777-6785 - [c93]Boyi Li, Felix Wu, Ser-Nam Lim, Serge J. Belongie
, Kilian Q. Weinberger:
On Feature Normalization and Data Augmentation. CVPR 2021: 12383-12392 - [c92]Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, Ser-Nam Lim:
Deep Co-Training with Task Decomposition for Semi-Supervised Domain Adaptation. ICCV 2021: 8886-8896 - [c91]Tianyi Zhang, Felix Wu, Arzoo Katiyar, Kilian Q. Weinberger, Yoav Artzi:
Revisiting Few-sample BERT Fine-tuning. ICLR 2021 - [c90]Johan Björck, Xiangyu Chen, Christopher De Sa, Carla P. Gomes, Kilian Q. Weinberger:
Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision. ICML 2021: 980-991 - [c89]Ruihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens van der Maaten, Kilian Q. Weinberger:
Making Paper Reviewing Robust to Bid Manipulation Attacks. ICML 2021: 11240-11250 - [c88]Johan Bjorck, Carla P. Gomes, Kilian Q. Weinberger:
Towards Deeper Deep Reinforcement Learning with Spectral Normalization. NeurIPS 2021: 8242-8255 - [c87]Ruihan Wu, Chuan Guo, Yi Su, Kilian Q. Weinberger:
Online Adaptation to Label Distribution Shift. NeurIPS 2021: 11340-11351 - [i67]Ruihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens van der Maaten, Kilian Q. Weinberger:
Making Paper Reviewing Robust to Bid Manipulation Attacks. CoRR abs/2102.06020 (2021) - [i66]Johan Bjorck, Xiangyu Chen, Christopher De Sa, Carla P. Gomes, Kilian Q. Weinberger:
Low-Precision Reinforcement Learning. CoRR abs/2102.13565 (2021) - [i65]Yurong You, Carlos Andres Diaz-Ruiz, Yan Wang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger:
Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection. CoRR abs/2103.14198 (2021) - [i64]Johan Bjorck, Carla P. Gomes, Kilian Q. Weinberger:
Towards Deeper Deep Reinforcement Learning. CoRR abs/2106.01151 (2021) - [i63]Ruihan Wu, Chuan Guo, Yi Su, Kilian Q. Weinberger:
Online Adaptation to Label Distribution Shift. CoRR abs/2107.04520 (2021) - [i62]Felix Wu, Kwangyoun Kim, Jing Pan, Kyu Jeong Han, Kilian Q. Weinberger, Yoav Artzi:
Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition. CoRR abs/2109.06870 (2021) - [i61]Johan Bjorck, Carla P. Gomes, Kilian Q. Weinberger:
Is High Variance Unavoidable in RL? A Case Study in Continuous Control. CoRR abs/2110.11222 (2021) - [i60]Cole Miles, Rhine Samajdar, Sepehr Ebadi, Tout T. Wang, Hannes Pichler, Subir Sachdev, Mikhail D. Lukin, Markus Greiner, Kilian Q. Weinberger, Eun-Ah Kim
:
Machine learning discovery of new phases in programmable quantum simulator snapshots. CoRR abs/2112.10789 (2021) - 2020
- [c86]Rui Qian, Divyansh Garg, Yan Wang, Yurong You
, Serge J. Belongie
, Bharath Hariharan, Mark E. Campbell
, Kilian Q. Weinberger, Wei-Lun Chao:
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection. CVPR 2020: 5880-5889 - [c85]Yan Wang, Xiangyu Chen, Yurong You
, Li Erran Li, Bharath Hariharan, Mark E. Campbell
, Kilian Q. Weinberger, Wei-Lun Chao:
Train in Germany, Test in the USA: Making 3D Object Detectors Generalize. CVPR 2020: 11710-11720 - [c84]Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving. ICLR 2020 - [c83]Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, Yoav Artzi:
BERTScore: Evaluating Text Generation with BERT. ICLR 2020 - [c82]Divyansh Garg, Yan Wang, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
Wasserstein Distances for Stereo Disparity Estimation. NeurIPS 2020 - [c81]Geoff Pleiss, Tianyi Zhang, Ethan R. Elenberg, Kilian Q. Weinberger:
Identifying Mislabeled Data using the Area Under the Margin Ranking. NeurIPS 2020 - [i59]Gao Huang, Zhuang Liu, Geoff Pleiss, Laurens van der Maaten, Kilian Q. Weinberger:
Convolutional Networks with Dense Connectivity. CoRR abs/2001.02394 (2020) - [i58]Geoff Pleiss, Tianyi Zhang, Ethan R. Elenberg, Kilian Q. Weinberger:
Identifying Mislabeled Data using the Area Under the Margin Ranking. CoRR abs/2001.10528 (2020) - [i57]Wei-Lun Chao, Han-Jia Ye, De-Chuan Zhan, Mark E. Campbell, Kilian Q. Weinberger:
Revisiting Meta-Learning as Supervised Learning. CoRR abs/2002.00573 (2020) - [i56]Chuan Guo, Ruihan Wu, Kilian Q. Weinberger:
TrojanNet: Embedding Hidden Trojan Horse Models in Neural Networks. CoRR abs/2002.10078 (2020) - [i55]Boyi Li, Felix Wu, Ser-Nam Lim, Serge J. Belongie, Kilian Q. Weinberger:
On Feature Normalization and Data Augmentation. CoRR abs/2002.11102 (2020) - [i54]Rui Qian, Divyansh Garg, Yan Wang, Yurong You, Serge J. Belongie, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection. CoRR abs/2004.03080 (2020) - [i53]Yan Wang, Xiangyu Chen, Yurong You, Li Erran Li, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
Train in Germany, Test in The USA: Making 3D Object Detectors Generalize. CoRR abs/2005.08139 (2020) - [i52]Tianyi Zhang, Felix Wu, Arzoo Katiyar, Kilian Q. Weinberger, Yoav Artzi:
Revisiting Few-sample BERT Fine-tuning. CoRR abs/2006.05987 (2020) - [i51]Divyansh Garg, Yan Wang, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
Wasserstein Distances for Stereo Disparity Estimation. CoRR abs/2007.03085 (2020) - [i50]Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, Ser-Nam Lim:
MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation. CoRR abs/2007.12684 (2020) - [i49]Cole Miles, Annabelle Bohrdt
, Ruihan Wu, Christie Chiu, Muqing Xu, Geoffrey Ji, Markus Greiner, Kilian Q. Weinberger, Eugene Demler, Eun-Ah Kim:
Correlator Convolutional Neural Networks: An Interpretable Architecture for Image-like Quantum Matter Data. CoRR abs/2011.03474 (2020) - [i48]Johan Bjorck, Kilian Q. Weinberger, Carla P. Gomes:
Understanding Decoupled and Early Weight Decay. CoRR abs/2012.13841 (2020)
2010 – 2019
- 2019
- [j10]Brian H. Wang
, Wei-Lun Chao, Yan Wang
, Bharath Hariharan, Kilian Q. Weinberger, Mark Campbell
:
LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images. IEEE Robotics Autom. Lett. 4(3): 2902-2909 (2019) - [c80]Carlos Diaz-Ruiz, Yan Wang, Wei-Lun Chao, Kilian Q. Weinberger, Mark E. Campbell:
Vision-only 3D Tracking for Self-Driving Cars. CASE 2019: 1029-1034 - [c79]Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark E. Campbell
, Kilian Q. Weinberger:
Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving. CVPR 2019: 8445-8453 - [c78]Chuan Guo, Jacob R. Gardner, Yurong You, Andrew Gordon Wilson, Kilian Q. Weinberger:
Simple Black-box Adversarial Attacks. ICML 2019: 2484-2493 - [c77]Felix Wu, Amauri H. Souza Jr., Tianyi Zhang, Christopher Fifty, Tao Yu, Kilian Q. Weinberger:
Simplifying Graph Convolutional Networks. ICML 2019: 6861-6871 - [c76]Yan Wang
, Zihang Lai, Gao Huang, Brian H. Wang, Laurens van der Maaten, Mark E. Campbell, Kilian Q. Weinberger:
Anytime Stereo Image Depth Estimation on Mobile Devices. ICRA 2019: 5893-5900 - [c75]Boyi Li, Felix Wu, Kilian Q. Weinberger, Serge J. Belongie:
Positional Normalization. NeurIPS 2019: 1620-1632 - [c74]Shengyuan Hu, Tao Yu, Chuan Guo, Wei-Lun Chao, Kilian Q. Weinberger:
A New Defense Against Adversarial Images: Turning a Weakness into a Strength. NeurIPS 2019: 1633-1644 - [c73]Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew Gordon Wilson:
Exact Gaussian Processes on a Million Data Points. NeurIPS 2019: 14622-14632 - [c72]Chuan Guo, Jared S. Frank, Kilian Q. Weinberger:
Low Frequency Adversarial Perturbation. UAI 2019: 1127-1137 - [i47]Zhixiang Eddie Xu, Gao Huang, Kilian Q. Weinberger, Alice X. Zheng:
Gradient Boosted Feature Selection. CoRR abs/1901.04055 (2019) - [i46]Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Alice X. Zheng:
Gradient Regularized Budgeted Boosting. CoRR abs/1901.04065 (2019) - [i45]Felix Wu, Tianyi Zhang, Amauri H. Souza Jr., Christopher Fifty, Tao Yu, Kilian Q. Weinberger:
Simplifying Graph Convolutional Networks. CoRR abs/1902.07153 (2019) - [i44]Felix Wu, Boyi Li, Lequn Wang, Ni Lao, John Blitzer, Kilian Q. Weinberger:
FastFusionNet: New State-of-the-Art for DAWNBench SQuAD. CoRR abs/1902.11291 (2019) - [i43]Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew Gordon Wilson:
Exact Gaussian Processes on a Million Data Points. CoRR abs/1903.08114 (2019) - [i42]Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, Yoav Artzi:
BERTScore: Evaluating Text Generation with BERT. CoRR abs/1904.09675 (2019) - [i41]Chuan Guo, Jacob R. Gardner, Yurong You, Andrew Gordon Wilson, Kilian Q. Weinberger:
Simple Black-box Adversarial Attacks. CoRR abs/1905.07121 (2019) - [i40]Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving. CoRR abs/1906.06310 (2019) - [i39]Boyi Li, Felix Wu, Kilian Q. Weinberger, Serge J. Belongie:
Positional Normalization. CoRR abs/1907.04312 (2019) - [i38]Felix Wu, Boyi Li, Lequn Wang, Ni Lao, John Blitzer, Kilian Q. Weinberger:
Integrated Triaging for Fast Reading Comprehension. CoRR abs/1909.13128 (2019) - [i37]Tao Yu, Shengyuan Hu, Chuan Guo, Wei-Lun Chao, Kilian Q. Weinberger:
A New Defense Against Adversarial Images: Turning a Weakness into a Strength. CoRR abs/1910.07629 (2019) - [i36]Brian H. Wang, Wei-Lun Chao, Yan Wang, Bharath Hariharan, Kilian Q. Weinberger, Mark E. Campbell:
LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images. CoRR abs/1910.13955 (2019) - [i35]Yan Wang, Wei-Lun Chao, Kilian Q. Weinberger, Laurens van der Maaten:
SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning. CoRR abs/1911.04623 (2019) - 2018
- [j9]Sheila A. McIlraith, Kilian Q. Weinberger, G. Michael Youngblood, Karen L. Myers, Eric Eaton, Michael Wollowski:
A Recap of the AAAI and IAAI 2018 Conferences and the EAAI Symposium. AI Mag. 39(4): 3-16 (2018) - [j8]Xilun Chen, Yu Sun, Ben Athiwaratkun, Claire Cardie, Kilian Q. Weinberger:
Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification. Trans. Assoc. Comput. Linguistics 6: 557-570 (2018) - [c71]Jacob R. Gardner, Geoff Pleiss, Ruihan Wu, Kilian Q. Weinberger, Andrew Gordon Wilson:
Product Kernel Interpolation for Scalable Gaussian Processes. AISTATS 2018: 1407-1416 - [c70]Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger:
CondenseNet: An Efficient DenseNet Using Learned Group Convolutions. CVPR 2018: 2752-2761 - [c69]Yan Wang, Lequn Wang, Yurong You
, Xu Zou, Vincent Chen, Serena Li, Gao Huang, Bharath Hariharan, Kilian Q. Weinberger:
Resource Aware Person Re-Identification Across Multiple Resolutions. CVPR 2018: 8042-8051 - [c68]Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, Kilian Q. Weinberger:
Multi-Scale Dense Networks for Resource Efficient Image Classification. ICLR 2018 - [c67]Geoff Pleiss, Jacob R. Gardner, Kilian Q. Weinberger, Andrew Gordon Wilson:
Constant-Time Predictive Distributions for Gaussian Processes. ICML 2018: 4111-4120 - [c66]Jacob R. Gardner, Geoff Pleiss, Kilian Q. Weinberger, David Bindel, Andrew Gordon Wilson:
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration. NeurIPS 2018: 7587-7597 - [c65]Johan Bjorck, Carla P. Gomes, Bart Selman, Kilian Q. Weinberger:
Understanding Batch Normalization. NeurIPS 2018: 7705-7716 - [e6]Sheila A. McIlraith, Kilian Q. Weinberger:
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-18), New Orleans, Louisiana, USA, February 2-7, 2018. AAAI Press 2018 [contents] - [i34]Jacob R. Gardner, Geoff Pleiss, Ruihan Wu, Kilian Q. Weinberger, Andrew Gordon Wilson:
Product Kernel Interpolation for Scalable Gaussian Processes. CoRR abs/1802.08903 (2018) - [i33]Geoff Pleiss, Jacob R. Gardner, Kilian Q. Weinberger, Andrew Gordon Wilson:
Constant-Time Predictive Distributions for Gaussian Processes. CoRR abs/1803.06058 (2018) - [i32]Yan Wang, Lequn Wang, Yurong You, Xu Zou, Vincent Chen, Serena Li, Gao Huang, Bharath Hariharan, Kilian Q. Weinberger:
Resource Aware Person Re-identification across Multiple Resolutions. CoRR abs/1805.08805 (2018) - [i31]Qiantong Xu, Gao Huang, Yang Yuan, Chuan Guo, Yu Sun, Felix Wu, Kilian Q. Weinberger:
An empirical study on evaluation metrics of generative adversarial networks. CoRR abs/1806.07755 (2018) - [i30]Chuan Guo, Jared S. Frank, Kilian Q. Weinberger:
Low Frequency Adversarial Perturbation. CoRR abs/1809.08758 (2018) - [i29]Jacob R. Gardner, Geoff Pleiss, David Bindel, Kilian Q. Weinberger, Andrew Gordon Wilson:
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration. CoRR abs/1809.11165 (2018) - [i28]Brian H. Wang, Yan Wang, Kilian Q. Weinberger, Mark Campbell:
Deep Person Re-identification for Probabilistic Data Association in Multiple Pedestrian Tracking. CoRR abs/1810.08565 (2018) - [i27]Yan Wang, Zihang Lai, Gao Huang, Brian H. Wang, Laurens van der Maaten, Mark Campbell, Kilian Q. Weinberger:
Anytime Stereo Image Depth Estimation on Mobile Devices. CoRR abs/1810.11408 (2018) - [i26]Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving. CoRR abs/1812.07179 (2018) - 2017
- [c64]Jacob R. Gardner, Chuan Guo, Kilian Q. Weinberger, Roman Garnett, Roger B. Grosse:
Discovering and Exploiting Additive Structure for Bayesian Optimization. AISTATS 2017: 1311-1319 - [c63]Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger:
Densely Connected Convolutional Networks. CVPR 2017: 2261-2269 - [c62]Paul Upchurch, Jacob R. Gardner, Geoff Pleiss, Robert Pless, Noah Snavely, Kavita Bala
, Kilian Q. Weinberger:
Deep Feature Interpolation for Image Content Changes. CVPR 2017: 6090-6099 - [c61]Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Q. Weinberger:
Snapshot Ensembles: Train 1, Get M for Free. ICLR (Poster) 2017 - [c60]Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger:
On Calibration of Modern Neural Networks. ICML 2017: 1321-1330 - [c59]Geoff Pleiss, Manish Raghavan, Felix Wu, Jon M. Kleinberg, Kilian Q. Weinberger:
On Fairness and Calibration. NIPS 2017: 5680-5689 - [i25]Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, Kilian Q. Weinberger:
Multi-Scale Dense Convolutional Networks for Efficient Prediction. CoRR abs/1703.09844 (2017) - [i24]Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Q. Weinberger:
Snapshot Ensembles: Train 1, get M for free. CoRR abs/1704.00109 (2017) - [i23]Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger:
On Calibration of Modern Neural Networks. CoRR abs/1706.04599 (2017) - [i22]Geoff Pleiss, Danlu Chen, Gao Huang, Tongcheng Li, Laurens van der Maaten, Kilian Q. Weinberger:
Memory-Efficient Implementation of DenseNets. CoRR abs/1707.06990 (2017) - [i21]Geoff Pleiss, Manish Raghavan, Felix Wu, Jon M. Kleinberg, Kilian Q. Weinberger:
On Fairness and Calibration. CoRR abs/1709.02012 (2017) - [i20]Felix Wu, Ni Lao, John Blitzer, Guandao Yang, Kilian Q. Weinberger:
Fast Reading Comprehension with ConvNets. CoRR abs/1711.04352 (2017) - [i19]Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger:
CondenseNet: An Efficient DenseNet using Learned Group Convolutions. CoRR abs/1711.09224 (2017) - 2016
- [c58]Matt J. Kusner, Yu Sun, Karthik Sridharan, Kilian Q. Weinberger:
Private Causal Inference. AISTATS 2016: 1308-1317 - [c57]Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Q. Weinberger:
Deep Networks with Stochastic Depth. ECCV (4) 2016: 646-661 - [c56]Wenlin Chen, James T. Wilson
, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen:
Compressing Convolutional Neural Networks in the Frequency Domain. KDD 2016: 1475-1484 - [c55]Gao Huang, Chuan Guo, Matt J. Kusner, Yu Sun, Fei Sha, Kilian Q. Weinberger:
Supervised Word Mover's Distance. NIPS 2016: 4862-4870 - [e5]Maria-Florina Balcan, Kilian Q. Weinberger:
Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016. JMLR Workshop and Conference Proceedings 48, JMLR.org 2016 [contents] - [i18]Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Q. Weinberger:
Deep Networks with Stochastic Depth. CoRR abs/1603.09382 (2016) - [i17]Xilun Chen, Ben Athiwaratkun, Yu Sun, Kilian Q. Weinberger, Claire Cardie:
Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification. CoRR abs/1606.01614 (2016) - [i16]Gao Huang, Zhuang Liu, Kilian Q. Weinberger:
Densely Connected Convolutional Networks. CoRR abs/1608.06993 (2016) - [i15]Paul Upchurch, Jacob R. Gardner, Kavita Bala, Robert Pless, Noah Snavely, Kilian Q. Weinberger:
Deep Feature Interpolation for Image Content Changes. CoRR abs/1611.05507 (2016) - 2015
- [j7]Minmin Chen, Kilian Q. Weinberger, Zhixiang Eddie Xu, Fei Sha:
Marginalizing stacked linear denoising autoencoders. J. Mach. Learn. Res. 16: 3849-3875 (2015) - [c54]Zheng Chen, Minmin Chen, Kilian Q. Weinberger, Weixiong Zhang:
Marginalized Denoising for Link Prediction and Multi-Label Learning. AAAI 2015: 1707-1713 - [c53]Quan Zhou, Wenlin Chen, Shiji Song, Jacob R. Gardner, Kilian Q. Weinberger, Yixin Chen:
A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing. AAAI 2015: 3210-3216 - [c52]Wenlin Chen, Yixin Chen, Kilian Q. Weinberger:
Filtered Search for Submodular Maximization with Controllable Approximation Bounds. AISTATS 2015 - [c51]Matt J. Kusner, Jacob R. Gardner, Roman Garnett, Kilian Q. Weinberger:
Differentially Private Bayesian Optimization. ICML 2015: 918-927 - [c50]Matt J. Kusner, Yu Sun, Nicholas I. Kolkin, Kilian Q. Weinberger:
From Word Embeddings To Document Distances. ICML 2015: 957-966 - [c49]Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen:
Compressing Neural Networks with the Hashing Trick. ICML 2015: 2285-2294 - [c48]Gustavo Malkomes, Matt J. Kusner, Wenlin Chen, Kilian Q. Weinberger, Benjamin Moseley:
Fast Distributed k-Center Clustering with Outliers on Massive Data. NIPS 2015: 1063-1071 - [c47]Jacob R. Gardner, Gustavo Malkomes, Roman Garnett, Kilian Q. Weinberger, Dennis L. Barbour, John P. Cunningham:
Bayesian Active Model Selection with an Application to Automated Audiometry. NIPS 2015: 2386-2394 - [c46]Jacob R. Gardner, Xinyu Song, Kilian Q. Weinberger, Dennis L. Barbour, John P. Cunningham:
Psychophysical Detection Testing with Bayesian Active Learning. UAI 2015: 286-295 - [i14]Zhixiang Eddie Xu, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger:
Compressed Support Vector Machines. CoRR abs/1501.06478 (2015) - [i13]Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen:
Compressing Neural Networks with the Hashing Trick. CoRR abs/1504.04788 (2015) - [i12]Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen:
Compressing Convolutional Neural Networks. CoRR abs/1506.04449 (2015) - [i11]Jacob R. Gardner, Matt J. Kusner, Yixuan Li, Paul Upchurch, Kilian Q. Weinberger, John E. Hopcroft:
Deep Manifold Traversal: Changing Labels with Convolutional Features. CoRR abs/1511.06421 (2015) - 2014
- [j6]Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, Olivier Chapelle:
Classifier cascades and trees for minimizing feature evaluation cost. J. Mach. Learn. Res. 15(1): 2113-2144 (2014) - [c45]Matt J. Kusner, Wenlin Chen, Quan Zhou, Zhixiang Eddie Xu, Kilian Q. Weinberger, Yixin Chen:
Feature-Cost Sensitive Learning with Submodular Trees of Classifiers. AAAI 2014: 1939-1945 - [c44]Matt J. Kusner, Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal:
Stochastic Neighbor Compression. ICML 2014: 622-630 - [c43]Jacob R. Gardner, Matt J. Kusner, Zhixiang Eddie Xu, Kilian Q. Weinberger, John P. Cunningham:
Bayesian Optimization with Inequality Constraints. ICML 2014: 937-945 - [c42]Minmin Chen, Kilian Q. Weinberger, Fei Sha, Yoshua Bengio:
Marginalized Denoising Auto-encoders for Nonlinear Representations. ICML 2014: 1476-1484 - [c41]Zhixiang Eddie Xu, Gao Huang, Kilian Q. Weinberger, Alice X. Zheng:
Gradient boosted feature selection. KDD 2014: 522-531 - [c40]Wenlin Chen, Yixin Chen, Kilian Q. Weinberger:
Fast flux discriminant for large-scale sparse nonlinear classification. KDD 2014: 621-630 - [c39]Gao Huang, Shiji Song, Zhixiang Eddie Xu, Kilian Q. Weinberger:
Transductive Minimax Probability Machine. ECML/PKDD (1) 2014: 579-594 - [e4]Zoubin Ghahramani, Max Welling, Corinna Cortes, Neil D. Lawrence, Kilian Q. Weinberger:
Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada. 2014 [contents] - [i10]Laurens van der Maaten, Minmin Chen, Stephen Tyree, Kilian Q. Weinberger:
Marginalizing Corrupted Features. CoRR abs/1402.7001 (2014) - [i9]Stephen Tyree, Jacob R. Gardner, Kilian Q. Weinberger, Kunal Agrawal, John Tran:
Parallel Support Vector Machines in Practice. CoRR abs/1404.1066 (2014) - [i8]Quan Zhou, Wenlin Chen, Shiji Song, Jacob R. Gardner, Kilian Q. Weinberger, Yixin Chen:
A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing. CoRR abs/1409.1976 (2014) - [i7]Matt J. Kusner, Nicholas I. Kolkin, Stephen Tyree, Kilian Q. Weinberger:
Stochastic Covariance Compression. CoRR abs/1412.1740 (2014) - 2013
- [c38]Wenlin Chen, Yixin Chen, Kilian Q. Weinberger, Qiang Lu, Xiaoping Chen:
Goal-Oriented Euclidean Heuristics with Manifold Learning. AAAI 2013: 173-179 - [c37]Qiang Lu, Wenlin Chen, Yixin Chen, Kilian Q. Weinberger, Xiaoping Chen:
Utilizing Landmarks in Euclidean Heuristics for Optimal Planning. AAAI (Late-Breaking Developments) 2013 - [c36]Fred W. Prior, Sarah Jost Fouke, Tammie L. S. Benzinger
, Alicia Boyd, Michael Chicoine, Sharath R. Cholleti, Matthew Kelsey, Bart Keogh, Lauren Kim, Mikhail Milchenko, David G. Politte, Stephen Tyree, Kilian Q. Weinberger, Daniel S. Marcus:
Predicting a multi-parametric probability map of active tumor extent using random forests. EMBC 2013: 6478-6481 - [c35]Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen:
Cost-Sensitive Tree of Classifiers. ICML (1) 2013: 133-141 - [c34]Wenlin Chen, Kilian Q. Weinberger, Yixin Chen:
Maximum Variance Correction with Application to A* Search. ICML (1) 2013: 302-310 - [c33]Laurens van der Maaten, Minmin Chen, Stephen Tyree, Kilian Q. Weinberger:
Learning with Marginalized Corrupted Features. ICML (1) 2013: 410-418 - [c32]Zhixiang Eddie Xu, Matt J. Kusner, Gao Huang, Kilian Q. Weinberger:
Anytime Representation Learning. ICML (3) 2013: 1076-1084 - [c31]Minmin Chen, Alice X. Zheng, Kilian Q. Weinberger:
Fast Image Tagging. ICML (3) 2013: 1274-1282 - [e3]Christopher J. C. Burges, Léon Bottou, Zoubin Ghahramani, Kilian Q. Weinberger:
Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States. 2013 [contents] - [i6]Zhixiang Eddie Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha:
An alternative text representation to TF-IDF and Bag-of-Words. CoRR abs/1301.6770 (2013) - 2012
- [c30]Zhixiang Eddie Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha:
From sBoW to dCoT marginalized encoders for text representation. CIKM 2012: 1879-1884 - [c29]Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha:
Marginalized Denoising Autoencoders for Domain Adaptation. ICML 2012 - [c28]Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle:
The Greedy Miser: Learning under Test-time Budgets. ICML 2012 - [c27]Laurens van der Maaten, Kilian Q. Weinberger:
Stochastic triplet embedding. MLSP 2012: 1-6 - [c26]Dor Kedem, Stephen Tyree, Kilian Q. Weinberger, Fei Sha, Gert R. G. Lanckriet:
Non-linear Metric Learning. NIPS 2012: 2582-2590 - [c25]Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle, Dor Kedem:
Classifier Cascade for Minimizing Feature Evaluation Cost. AISTATS 2012: 218-226 - [e2]Peter L. Bartlett, Fernando C. N. Pereira, Christopher J. C. Burges, Léon Bottou, Kilian Q. Weinberger:
Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States. 2012 [contents] - [i5]Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha:
Marginalized Denoising Autoencoders for Domain Adaptation. CoRR abs/1206.4683 (2012) - [i4]Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle:
Distance Metric Learning for Kernel Machines. CoRR abs/1208.3422 (2012) - [i3]Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen:
Cost-Sensitive Tree of Classifiers. CoRR abs/1210.2771 (2012) - 2011
- [j5]Olivier Chapelle, Pannagadatta K. Shivaswamy, Srinivas Vadrevu, Kilian Q. Weinberger, Ya Zhang
, Belle L. Tseng:
Boosted multi-task learning. Mach. Learn. 85(1-2): 149-173 (2011) - [c24]Anirudh Ramachandran, Anirban Dasgupta
, Nick Feamster, Kilian Q. Weinberger:
Spam or ham?: characterizing and detecting fraudulent "not spam" reports in web mail systems. CEAS 2011: 210-219 - [c23]Minmin Chen, Kilian Q. Weinberger, Yixin Chen:
Automatic Feature Decomposition for Single View Co-training. ICML 2011: 953-960 - [c22]Minmin Chen, Kilian Q. Weinberger, John Blitzer:
Co-Training for Domain Adaptation. NIPS 2011: 2456-2464 - [c21]Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal, Jennifer Paykin:
Parallel boosted regression trees for web search ranking. WWW 2011: 387-396 - [c20]Ananth Mohan, Zheng Chen, Kilian Q. Weinberger:
Web-Search Ranking with Initialized Gradient Boosted Regression Trees. Yahoo! Learning to Rank Challenge 2011: 77-89 - [e1]John Shawe-Taylor, Richard S. Zemel, Peter L. Bartlett, Fernando C. N. Pereira, Kilian Q. Weinberger:
Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, Granada, Spain. 2011 [contents] - [i2]Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha:
Rapid Feature Learning with Stacked Linear Denoisers. CoRR abs/1105.0972 (2011) - 2010
- [j4]Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Olivier Chapelle, Kilian Q. Weinberger:
Learning to rank with (a lot of) word features. Inf. Retr. 13(3): 291-314 (2010) - [j3]Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul:
Convex Optimizations for Distance Metric Learning and Pattern Classification [Applications Corner]. IEEE Signal Process. Mag. 27(3): 146-158 (2010) - [c19]Olivier Chapelle, Pannagadatta K. Shivaswamy, Srinivas Vadrevu, Kilian Q. Weinberger, Ya Zhang
, Belle L. Tseng:
Multi-task learning for boosting with application to web search ranking. KDD 2010: 1189-1198 - [c18]Yuzong Liu, Mohit Sharma, Charles M. Gaona, Jonathan Breshears, Jarod Roland, Zachary Freudenburg, Kilian Q. Weinberger, Eric Leuthardt:
Decoding Ipsilateral Finger Movements from ECoG Signals in Humans. NIPS 2010: 1468-1476 - [c17]Shibin Parameswaran, Kilian Q. Weinberger:
Large Margin Multi-Task Metric Learning. NIPS 2010: 1867-1875
2000 – 2009
- 2009
- [j2]Kilian Q. Weinberger, Lawrence K. Saul:
Distance Metric Learning for Large Margin Nearest Neighbor Classification. J. Mach. Learn. Res. 10: 207-244 (2009) - [c16]Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Olivier Chapelle, Kilian Q. Weinberger:
Supervised semantic indexing. CIKM 2009: 187-196 - [c15]Kilian Q. Weinberger, Anirban Dasgupta
, John Langford, Alexander J. Smola, Josh Attenberg:
Feature hashing for large scale multitask learning. ICML 2009: 1113-1120 - [c14]Eva Hörster, Malcolm Slaney
, Marc'Aurelio Ranzato, Kilian Q. Weinberger:
Unsupervised image ranking. LS-MMRM@ACM Multimedia 2009: 81-88 - [i1]Kilian Q. Weinberger, Anirban Dasgupta, Josh Attenberg, John Langford, Alexander J. Smola:
Feature Hashing for Large Scale Multitask Learning. CoRR abs/0902.2206 (2009) - 2008
- [c13]Kilian Q. Weinberger, Lawrence K. Saul:
Fast solvers and efficient implementations for distance metric learning. ICML 2008: 1160-1167 - [c12]Joshua M. Lewis, Pincelli M. Hull, Kilian Q. Weinberger, Lawrence K. Saul:
Mapping Uncharted Waters: Exploratory Analysis, Visualization, and Clustering of Oceanographic Data. ICMLA 2008: 388-395 - [c11]Malcolm Slaney, Kilian Q. Weinberger, William White:
Learning a Metric for Music Similarity. ISMIR 2008: 313-318 - [c10]Kilian Q. Weinberger, Malcolm Slaney
, Roelof van Zwol:
Resolving tag ambiguity. ACM Multimedia 2008: 111-120 - [c9]Kilian Q. Weinberger, Olivier Chapelle:
Large Margin Taxonomy Embedding for Document Categorization. NIPS 2008: 1737-1744 - 2007
- [c8]Kilian Q. Weinberger, Gerald Tesauro:
Metric Learning for Kernel Regression. AISTATS 2007: 612-619 - 2006
- [j1]Kilian Q. Weinberger, Lawrence K. Saul:
Unsupervised Learning of Image Manifolds by Semidefinite Programming. Int. J. Comput. Vis. 70(1): 77-90 (2006) - [c7]Kilian Q. Weinberger, Lawrence K. Saul:
An Introduction to Nonlinear Dimensionality Reduction by Maximum Variance Unfolding. AAAI 2006: 1683-1686 - [c6]Kilian Q. Weinberger, Fei Sha, Qihui Zhu, Lawrence K. Saul:
Graph Laplacian Regularization for Large-Scale Semidefinite Programming. NIPS 2006: 1489-1496 - [p1]Lawrence K. Saul, Kilian Q. Weinberger, Fei Sha, Jihun Ham, Daniel D. Lee:
Spectral Methods for Dimensionality Reduction. Semi-Supervised Learning 2006: 292-308 - 2005
- [c5]Kilian Q. Weinberger, Benjamin Packer, Lawrence K. Saul:
Nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization. AISTATS 2005: 381-388 - [c4]Kilian Q. Weinberger, John Blitzer, Lawrence K. Saul:
Distance Metric Learning for Large Margin Nearest Neighbor Classification. NIPS 2005: 1473-1480 - 2004
- [c3]Kilian Q. Weinberger, Lawrence K. Saul:
Unsupervised Learning of Image Manifolds by Semidefinite Programming. CVPR (2) 2004: 988-995 - [c2]Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul:
Learning a kernel matrix for nonlinear dimensionality reduction. ICML 2004 - [c1]John Blitzer, Kilian Q. Weinberger, Lawrence K. Saul, Fernando Pereira:
Hierarchical Distributed Representations for Statistical Language Modeling. NIPS 2004: 185-192
Coauthor Index
![](https://dblp.org/img/cog.dark.24x24.png)
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