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ORCIDEric P. Xing
Eric Po Xing
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- affiliation: Carnegie Mellon University, School of Computer Science, Pittsburgh, PA, USA
- affiliation: Petuum Inc., Pittsburgh, PA, USA
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2020 – today
- 2023
[i218]Song Bian, Dacheng Li, Hongyi Wang, Eric P. Xing, Shivaram Venkataraman:
Does compressing activations help model parallel training? CoRR abs/2301.02654 (2023)- [i217]Han Guo, Philip Greengard, Hongyi Wang, Andrew Gelman, Yoon Kim, Eric P. Xing:
Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach. CoRR abs/2302.04228 (2023) - [i216]Kai Zhang, Yutong Dai, Hongyi Wang, Eric P. Xing, Xun Chen, Lichao Sun:
Memory-adaptive Depth-wise Heterogenous Federated Learning. CoRR abs/2303.04887 (2023) - [i215]Kunhao Liu, Fangneng Zhan, Yiwen Chen, Jiahui Zhang, Yingchen Yu, Abdulmotaleb El-Saddik, Shijian Lu, Eric P. Xing:
StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fields. CoRR abs/2303.10598 (2023) - [i214]Kaiwen Cui, Yingchen Yu, Fangneng Zhan, Shengcai Liao, Shijian Lu, Eric P. Xing:
KD-DLGAN: Data Limited Image Generation via Knowledge Distillation. CoRR abs/2303.17158 (2023) - [i213]Aoran Xiao, Jiaxing Huang, Weihao Xuan, Ruijie Ren, Kangcheng Liu, Dayan Guan, Abdulmotaleb El-Saddik, Shijian Lu, Eric P. Xing:
3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds. CoRR abs/2304.00690 (2023) - [i212]Hongyi Wang, Saurabh Agarwal, Pongsakorn U.-Chupala, Yoshiki Tanaka, Eric P. Xing, Dimitris S. Papailiopoulos:
Cuttlefish: Low-Rank Model Training without All the Tuning. CoRR abs/2305.02538 (2023) - [i211]Hanlin Zhang, Jiani Huang, Ziyang Li, Mayur Naik, Eric P. Xing:
Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming. CoRR abs/2305.03742 (2023) - 2022
- [j68]Nanqing Dong
, Michael Kampffmeyer, Xiaodan Liang, Min Xu, Irina Voiculescu, Eric P. Xing:
Towards robust partially supervised multi-structure medical image segmentation on small-scale data. Appl. Soft Comput. 114: 108074 (2022) - [j67]Haohan Wang, Bryon Aragam, Eric P. Xing:
Trade-offs of Linear Mixed Models in Genome-Wide Association Studies. J. Comput. Biol. 29(3): 233-242 (2022) - [j66]Haohan Wang, Oscar Lopez, Eric P. Xing, Wei Wu:
Kernel Mixed Model for Transcriptome Association Study. J. Comput. Biol. 29(12): 1353-1356 (2022) - [j65]Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric P. Xing:
Negational symmetry of quantum neural networks for binary pattern classification. Pattern Recognit. 129: 108750 (2022) - [j64]Zeya Wang, Yang Ni, Baoyu Jing, Deqing Wang, Hao Zhang, Eric P. Xing:
DNB: A Joint Learning Framework for Deep Bayesian Nonparametric Clustering. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7610-7620 (2022) - [c339]Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell, Eric Po Xing:
Un-mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning. AAAI 2022: 2216-2224 - [c338]Bhanu Garg, Li Zhang, Pradyumna Sridhara, Ramtin Hosseini, Eric P. Xing, Pengtao Xie:
Learning from Mistakes - a Framework for Neural Architecture Search. AAAI 2022: 10184-10192 - [c337]Benjamin J. Lengerich, Eric P. Xing, Rich Caruana:
Dropout as a Regularizer of Interaction Effects. AISTATS 2022: 7550-7564 - [c336]Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing:
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. CVPR 2022: 4921-4931 - [c335]Zechun Liu, Kwang-Ting Cheng, Dong Huang, Eric P. Xing, Zhiqiang Shen:
Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation. CVPR 2022: 4932-4942 - [c334]Hanlin Zhang, Yi-Fan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric P. Xing:
Towards Principled Disentanglement for Domain Generalization. CVPR 2022: 8014-8024 - [c333]Zeyi Huang, Haohan Wang, Dong Huang, Yong Jae Lee, Eric P. Xing:
The Two Dimensions of Worst-case Training and Their Integrated Effect for Out-of-domain Generalization. CVPR 2022: 9621-9631 - [c332]Zechun Liu, Zhiqiang Shen, Yun Long, Eric P. Xing, Kwang-Ting Cheng, Chas Leichner:
Data-Free Neural Architecture Search via Recursive Label Calibration. ECCV (24) 2022: 391-406 - [c331]Zhiqiang Shen, Eric P. Xing:
A Fast Knowledge Distillation Framework for Visual Recognition. ECCV (24) 2022: 673-690 - [c330]Zhiqiang Shen, Zechun Liu, Eric P. Xing:
Sliced Recursive Transformer. ECCV (24) 2022: 727-744 - [c329]Jiannan Xiang, Zhengzhong Liu, Yucheng Zhou, Eric P. Xing, Zhiting Hu:
ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Models. EMNLP (Findings) 2022: 1886-1899 - [c328]Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, Yihan Wang, Han Guo, Tianmin Shu, Meng Song, Eric P. Xing, Zhiting Hu:
RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning. EMNLP 2022: 3369-3391 - [c327]Han Guo, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu:
Efficient (Soft) Q-Learning for Text Generation with Limited Good Data. EMNLP (Findings) 2022: 6969-6991 - [c326]Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric P. Xing, Kwang-Ting Cheng:
SDQ: Stochastic Differentiable Quantization with Mixed Precision. ICML 2022: 9295-9309 - [c325]Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing:
Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation. KDD 2022: 1846-1856 - [c324]Kartik Sreenivasan, Jy-yong Sohn, Liu Yang, Matthew Grinde, Alliot Nagle, Hongyi Wang, Eric P. Xing, Kangwook Lee, Dimitris S. Papailiopoulos:
Rare Gems: Finding Lottery Tickets at Initialization. NeurIPS 2022 - [c323]Lianmin Zheng, Zhuohan Li, Hao Zhang, Yonghao Zhuang, Zhifeng Chen, Yanping Huang, Yida Wang, Yuanzhong Xu, Danyang Zhuo, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica:
Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning. OSDI 2022: 559-578 - [c322]Haohan Wang, Oscar L. Lopez, Wei Wu, Eric P. Xing:
Gene Set Priorization Guided by Regulatory Networks with p-values through Kernel Mixed Model. RECOMB 2022: 107-125 - [c321]Haohan Wang, Zeyi Huang, Hanlin Zhang, Yong Jae Lee, Eric P. Xing:
Toward learning human-aligned cross-domain robust models by countering misaligned features. UAI 2022: 2075-2084 - [i210]Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing:
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. CoRR abs/2201.00814 (2022) - [i209]Ziyin Liu, Hanlin Zhang, Xiangming Meng, Yuting Lu, Eric P. Xing, Masahito Ueda:
Stochastic Neural Networks with Infinite Width are Deterministic. CoRR abs/2201.12724 (2022) - [i208]Yi-Fan Zhang, Hanlin Zhang, Zachary C. Lipton, Li Erran Li, Eric P. Xing:
Can Transformers be Strong Treatment Effect Estimators? CoRR abs/2202.01336 (2022) - [i207]Zeyi Huang, Haohan Wang, Dong Huang, Yong Jae Lee, Eric P. Xing:
The Two Dimensions of Worst-case Training and the Integrated Effect for Out-of-domain Generalization. CoRR abs/2204.04384 (2022) - [i206]Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, Yihan Wang, Han Guo, Tianmin Shu, Meng Song, Eric P. Xing, Zhiting Hu:
RLPrompt: Optimizing Discrete Text Prompts With Reinforcement Learning. CoRR abs/2205.12548 (2022) - [i205]Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing:
Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation. CoRR abs/2206.01909 (2022) - [i204]Xijie Huang, Zhiqiang Shen, Shichao Li, Zechun Liu, Xianghong Hu, Jeffry Wicaksana, Eric P. Xing, Kwang-Ting Cheng:
SDQ: Stochastic Differentiable Quantization with Mixed Precision. CoRR abs/2206.04459 (2022) - [i203]Shibo Hao, Bowen Tan, Kaiwen Tang, Hengzhe Zhang, Eric P. Xing, Zhiting Hu:
BertNet: Harvesting Knowledge Graphs from Pretrained Language Models. CoRR abs/2206.14268 (2022) - [i202]Sang Keun Choe, Willie Neiswanger, Pengtao Xie, Eric P. Xing:
Betty: An Automatic Differentiation Library for Multilevel Optimization. CoRR abs/2207.02849 (2022) - [i201]Yifan Zhong, Haohan Wang, Eric P. Xing:
MRCLens: an MRC Dataset Bias Detection Toolkit. CoRR abs/2207.08943 (2022) - [i200]Chonghan Chen, Haohan Wang, Leyang Hu, Yuhao Zhang, Shuguang Lyu, Jingcheng Wu, Xinnuo Li, Linjing Sun, Eric P. Xing:
Robustar: Interactive Toolbox Supporting Precise Data Annotation for Robust Vision Learning. CoRR abs/2207.08944 (2022) - [i199]Gongjie Zhang, Zhipeng Luo, Yingchen Yu, Jiaxing Huang, Kaiwen Cui, Shijian Lu, Eric P. Xing:
Semantic-Aligned Matching for Enhanced DETR Convergence and Multi-Scale Feature Fusion. CoRR abs/2207.14172 (2022) - [i198]Gongjie Zhang, Zhipeng Luo, Kaiwen Cui, Shijian Lu, Eric P. Xing:
Meta-DETR: Image-Level Few-Shot Detection with Inter-Class Correlation Exploitation. CoRR abs/2208.00219 (2022) - [i197]Jiannan Xiang, Zhengzhong Liu, Yucheng Zhou, Eric P. Xing, Zhiting Hu:
ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Models. CoRR abs/2210.04325 (2022) - [i196]Dacheng Li, Hongyi Wang, Eric P. Xing, Hao Zhang:
AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness. CoRR abs/2210.07297 (2022) - [i195]Kirill Vishniakov, Eric P. Xing, Zhiqiang Shen:
MixMask: Revisiting Masked Siamese Self-supervised Learning in Asymmetric Distance. CoRR abs/2210.11456 (2022) - [i194]Dacheng Li, Rulin Shao, Hongyi Wang, Han Guo, Eric P. Xing, Hao Zhang:
MPCFormer: fast, performant and private Transformer inference with MPC. CoRR abs/2211.01452 (2022) - [i193]Yonghao Zhuang, Hexu Zhao, Lianmin Zheng, Zhuohan Li, Eric P. Xing, Qirong Ho, Joseph E. Gonzalez, Ion Stoica, Hao Zhang:
On Optimizing the Communication of Model Parallelism. CoRR abs/2211.05322 (2022) - [i192]Minh-Long Luu, Zeyi Huang, Eric P. Xing, Yong Jae Lee, Haohan Wang:
Expeditious Saliency-guided Mix-up through Random Gradient Thresholding. CoRR abs/2212.04875 (2022) - [i191]Hanlin Zhang, Yi-Fan Zhang, Li Erran Li, Eric P. Xing:
The Impact of Symbolic Representations on In-context Learning for Few-shot Reasoning. CoRR abs/2212.08686 (2022) - 2021
- [j63]Xuefeng Du, Haohan Wang, Zhenxi Zhu, Xiangrui Zeng, Yi-Wei Chang, Jing Zhang, Eric P. Xing, Min Xu:
Active learning to classify macromolecular structures in situ for less supervision in cryo-electron tomography. Bioinform. 37(16): 2340-2346 (2021) - [j62]Haohan Wang, Fen Pei, Michael M. Vanyukov, Ivet Bahar, Wei Wu, Eric P. Xing:
Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets. BMC Bioinform. 22(1): 50 (2021) - [c320]Seo-Jin Bang, Pengtao Xie, Heewook Lee, Wei Wu, Eric P. Xing:
Explaining A Black-box By Using A Deep Variational Information Bottleneck Approach. AAAI 2021: 11396-11404 - [c319]Jiaqi Chen, Jianheng Tang, Jinghui Qin, Xiaodan Liang, Lingbo Liu, Eric P. Xing, Liang Lin:
GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning. ACL/IJCNLP (Findings) 2021: 513-523 - [c318]Xuehai He, Zhuo Cai, Wenlan Wei, Yichen Zhang, Luntian Mou, Eric P. Xing, Pengtao Xie:
Towards Visual Question Answering on Pathology Images. ACL/IJCNLP (2) 2021: 708-718 - [c317]Meng Zhou, Zechen Li, Bowen Tan, Guangtao Zeng, Wenmian Yang, Xuehai He, Zeqian Ju, Subrato Chakravorty, Shu Chen, Xingyi Yang, Yichen Zhang, Qingyang Wu, Zhou Yu, Kun Xu, Eric P. Xing, Pengtao Xie:
On the Generation of Medical Dialogs for COVID-19. ACL/IJCNLP (2) 2021: 886-896 - [c316]Maruan Al-Shedivat, Liam Li, Eric P. Xing, Ameet Talwalkar:
On Data Efficiency of Meta-learning. AISTATS 2021: 1369-1377 - [c315]Huaxiu Yao, Yingxin Wu, Maruan Al-Shedivat, Eric P. Xing:
Knowledge-Aware Meta-learning for Low-Resource Text Classification. EMNLP (1) 2021: 1814-1821 - [c314]Mingkai Deng, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu:
Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation. EMNLP (1) 2021: 7580-7605 - [c313]Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh:
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. ICLR 2021 - [c312]Benedikt Boecking, Willie Neiswanger, Eric P. Xing, Artur Dubrawski:
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling. ICLR 2021 - [c311]Bowen Tan, Zichao Yang, Maruan Al-Shedivat, Eric P. Xing, Zhiting Hu:
Progressive Generation of Long Text with Pretrained Language Models. NAACL-HLT 2021: 4313-4324 - [c310]Xinshi Chen, Haoran Sun, Caleb Ellington, Eric P. Xing, Le Song:
Multi-task Learning of Order-Consistent Causal Graphs. NeurIPS 2021: 11083-11095 - [c309]Aurick Qiao, Sang Keun Choe, Suhas Jayaram Subramanya, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R. Ganger, Eric P. Xing:
Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. OSDI 2021 - [i190]Alexander Lavin, Ciarán M. Gilligan-Lee, Alessya Visnjic, Siddha Ganju, Dava Newman, Sujoy Ganguly, Danny Lange, Atilim Günes Baydin, Amit Sharma, Adam Gibson, Yarin Gal, Eric P. Xing, Chris Mattmann, James Parr:
Technology Readiness Levels for Machine Learning Systems. CoRR abs/2101.03989 (2021) - [i189]Maruan Al-Shedivat, Liam Li, Eric Po Xing, Ameet Talwalkar:
On Data Efficiency of Meta-learning. CoRR abs/2102.00127 (2021) - [i188]Xuefeng Du, Haohan Wang, Zhenxi Zhu, Xiangrui Zeng, Yi-Wei Chang, Jing Zhang, Eric Po Xing, Min Xu:
Active Learning to Classify Macromolecular Structures in situ for Less Supervision in Cryo-Electron Tomography. CoRR abs/2102.12040 (2021) - [i187]Zhengzhong Liu, Guanxiong Ding, Avinash Bukkittu, Mansi Gupta, Pengzhi Gao, Atif Ahmed, Shikun Zhang, Xin Gao, Swapnil Singhavi, Linwei Li, Wei Wei, Zecong Hu, Haoran Shi, Xiaodan Liang, Teruko Mitamura, Eric P. Xing, Zhiting Hu:
A Data-Centric Framework for Composable NLP Workflows. CoRR abs/2103.01834 (2021) - [i186]Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric P. Xing:
Negational Symmetry of Quantum Neural Networks for Binary Pattern Classification. CoRR abs/2105.09580 (2021) - [i185]Jiaqi Chen, Jianheng Tang, Jinghui Qin, Xiaodan Liang, Lingbo Liu, Eric P. Xing, Liang Lin:
GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning. CoRR abs/2105.14517 (2021) - [i184]Han Guo, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu:
Text Generation with Efficient (Soft) Q-Learning. CoRR abs/2106.07704 (2021) - [i183]Yuxin Xiao, Eric P. Xing, Willie Neiswanger:
Amortized Auto-Tuning: Cost-Efficient Transfer Optimization for Hyperparameter Recommendation. CoRR abs/2106.09179 (2021) - [i182]Shuai Lin, Pan Zhou, Zi-Yuan Hu, Shuojia Wang, Ruihui Zhao, Yefeng Zheng, Liang Lin, Eric P. Xing, Xiaodan Liang:
Prototypical Graph Contrastive Learning. CoRR abs/2106.09645 (2021) - [i181]Zhiting Hu, Eric P. Xing:
Panoramic Learning with A Standardized Machine Learning Formalism. CoRR abs/2108.07783 (2021) - [i180]Huaxiu Yao, Yingxin Wu, Maruan Al-Shedivat, Eric P. Xing:
Knowledge-Aware Meta-learning for Low-Resource Text Classification. CoRR abs/2109.04707 (2021) - [i179]Mingkai Deng, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu:
Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation. CoRR abs/2109.06379 (2021) - [i178]Zhaoming Qin, Nanqing Dong, Eric P. Xing, Junwei Cao:
Cooperative Multi-Agent Actor-Critic for Privacy-Preserving Load Scheduling in a Residential Microgrid. CoRR abs/2110.02784 (2021) - [i177]Shentong Mo, Xi Fu, Chenyang Hong, Yizhen Chen, Yuxuan Zheng, Xiangru Tang, Zhiqiang Shen, Eric P. Xing, Yanyan Lan:
Multi-modal Self-supervised Pre-training for Regulatory Genome Across Cell Types. CoRR abs/2110.05231 (2021) - [i176]Benjamin J. Lengerich, Caleb Ellington, Bryon Aragam, Eric P. Xing, Manolis Kellis:
NOTMAD: Estimating Bayesian Networks with Sample-Specific Structures and Parameters. CoRR abs/2111.01104 (2021) - [i175]Xinshi Chen, Haoran Sun, Caleb Ellington, Eric P. Xing, Le Song:
Multi-task Learning of Order-Consistent Causal Graphs. CoRR abs/2111.02545 (2021) - [i174]Haohan Wang, Bryon Aragam, Eric P. Xing:
Tradeoffs of Linear Mixed Models in Genome-wide Association Studies. CoRR abs/2111.03739 (2021) - [i173]Haohan Wang, Zeyi Huang, Hanlin Zhang, Eric Po Xing:
Toward Learning Human-aligned Cross-domain Robust Models by Countering Misaligned Features. CoRR abs/2111.03740 (2021) - [i172]Zhiqiang Shen, Zechun Liu, Eric P. Xing:
Sliced Recursive Transformer. CoRR abs/2111.05297 (2021) - [i171]Bhanu Garg, Li Zhang, Pradyumna Sridhara, Ramtin Hosseini, Eric P. Xing, Pengtao Xie:
Learning from Mistakes - A Framework for Neural Architecture Search. CoRR abs/2111.06353 (2021) - [i170]Hanlin Zhang, Yi-Fan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric P. Xing:
Towards Principled Disentanglement for Domain Generalization. CoRR abs/2111.13839 (2021) - [i169]Zechun Liu, Kwang-Ting Cheng, Dong Huang, Eric P. Xing, Zhiqiang Shen:
Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation. CoRR abs/2111.14826 (2021) - [i168]Zhiqiang Shen, Eric P. Xing:
A Fast Knowledge Distillation Framework for Visual Recognition. CoRR abs/2112.01528 (2021) - [i167]Zechun Liu, Zhiqiang Shen, Yun Long, Eric P. Xing, Kwang-Ting Cheng, Chas Leichner:
Data-Free Neural Architecture Search via Recursive Label Calibration. CoRR abs/2112.02086 (2021) - 2020
- [j61]Shreya Kadambi, Zeya Wang, Eric P. Xing:
WGAN domain adaptation for the joint optic disc-and-cup segmentation in fundus images. Int. J. Comput. Assist. Radiol. Surg. 15(7): 1205-1213 (2020) - [j60]Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria, Christopher R. Collins, Jeff Schneider, Barnabás Póczos, Eric P. Xing:
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly. J. Mach. Learn. Res. 21: 81:1-81:27 (2020) - [j59]Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing:
Contextual Explanation Networks. J. Mach. Learn. Res. 21: 194:1-194:44 (2020) - [j58]Kevin Tran, Willie Neiswanger, Junwoong Yoon, Qingyang Zhang, Eric P. Xing, Zachary W. Ulissi:
Methods for comparing uncertainty quantifications for material property predictions. Mach. Learn. Sci. Technol. 1(2): 25006 (2020) - [j57]Yumin Zheng, Haohan Wang, Yang Zhang, Xin Gao, Eric P. Xing, Min Xu:
Poly(A)-DG: A deep-learning-based domain generalization method to identify cross-species Poly(A) signal without prior knowledge from target species. PLoS Comput. Biol. 16(11): 1008297 (2020) - [j56]Yujia Zhang, Xiaodan Liang, Dingwen Zhang, Min Tan, Eric P. Xing:
Unsupervised object-level video summarization with online motion auto-encoder. Pattern Recognit. Lett. 130: 376-385 (2020) - [c308]Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy, Willie Neiswanger, Barnabás Póczos, Jeff Schneider, Eric P. Xing:
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations. AISTATS 2020: 3393-3403 - [c307]Xun Zheng, Chen Dan, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing:
Learning Sparse Nonparametric DAGs. AISTATS 2020: 3414-3425 - [c306]Kumar Avinava Dubey, Michael Minyi Zhang, Eric P. Xing, Sinead Williamson:
Distributed, partially collapsed MCMC for Bayesian Nonparametrics. AISTATS 2020: 3685-3695 - [c305]Haohan Wang, Xindi Wu, Zeyi Huang, Eric P. Xing:
High-Frequency Component Helps Explain the Generalization of Convolutional Neural Networks. CVPR 2020: 8681-8691 - [c304]Zeya Wang, Baoyu Jing, Yang Ni, Nanqing Dong, Pengtao Xie, Eric P. Xing:
Adversarial Domain Adaptation Being Aware of Class Relationships. ECAI 2020: 1579-1586 - [c303]Zeyi Huang, Haohan Wang, Eric P. Xing, Dong Huang:
Self-challenging Improves Cross-Domain Generalization. ECCV (2) 2020: 124-140 - [c302]Zhengzhong Liu, Guanxiong Ding, Avinash Bukkittu, Mansi Gupta, Pengzhi Gao, Atif Ahmed, Shikun Zhang, Xin Gao, Swapnil Singhavi, Linwei Li, Wei Wei, Zecong Hu, Haoran Shi, Xiaodan Liang, Teruko Mitamura, Eric P. Xing, Zhiting Hu:
A Data-Centric Framework for Composable NLP Workflows. EMNLP (Demos) 2020: 197-204 - [c301]Shuai Lin, Wentao Wang, Zichao Yang, Xiaodan Liang, Frank F. Xu, Eric P. Xing, Zhiting Hu:
Record-to-Text Generation with Style Imitation. EMNLP (Findings) 2020: 1589-1598 - [c300]Bowen Tan, Lianhui Qin, Eric P. Xing, Zhiting Hu:
Summarizing Text on Any Aspects: A Knowledge-Informed Weakly-Supervised Approach. EMNLP (1) 2020: 6301-6309 - [c299]Congzheng Song, Shanghang Zhang, Najmeh Sadoughi, Pengtao Xie, Eric P. Xing:
Generalized Zero-Shot Text Classification for ICD Coding. IJCAI 2020: 4018-4024 - [c298]Zhiting Hu, Eric P. Xing:
Learning from All Types of Experiences: A Unifying Machine Learning Perspective. KDD 2020: 3531-3532 - [c297]Hao Zhang, Yuan Li, Zhijie Deng, Xiaodan Liang, Lawrence Carin, Eric P. Xing:
AutoSync: Learning to Synchronize for Data-Parallel Distributed Deep Learning. NeurIPS 2020 - [c296]Gregory Plumb, Maruan Al-Shedivat, Ángel Alexander Cabrera, Adam Perer, Eric P. Xing, Ameet Talwalkar:
Regularizing Black-box Models for Improved Interpretability. NeurIPS 2020 - [c295]Yue Wu, Pan Zhou, Andrew Gordon Wilson, Eric P. Xing, Zhiting Hu:
Improving GAN Training with Probability Ratio Clipping and Sample Reweighting. NeurIPS 2020 - [c294]Songwei Ge, Haohan Wang, Amir Alavi, Eric P. Xing, Ziv Bar-Joseph:
Supervised Adversarial Alignment of Single-Cell RNA-seq Data. RECOMB 2020: 72-87 - [i166]Avinava Dubey, Michael Minyi Zhang, Eric P. Xing, Sinead A. Williamson:
Distributed, partially collapsed MCMC for Bayesian Nonparametrics. CoRR abs/2001.05591 (2020) - [i165]Xuehai He, Yichen Zhang, Luntian Mou, Eric P. Xing, Pengtao Xie:
PathVQA: 30000+ Questions for Medical Visual Question Answering. CoRR abs/2003.10286 (2020) - [i164]Emmanouil Antonios Platanios, Maruan Al-Shedivat, Eric P. Xing, Tom M. Mitchell:
Learning from Imperfect Annotations. CoRR abs/2004.03473 (2020) - [i163]Baoyu Jing, Zeya Wang, Eric P. Xing:
Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-Ray Reports. CoRR abs/2004.12274 (2020) - [i162]Wenmian Yang, Guangtao Zeng, Bowen Tan, Zeqian Ju, Subrato Chakravorty, Xuehai He, Shu Chen, Xingyi Yang, Qingyang Wu, Zhou Yu, Eric P. Xing, Pengtao Xie:
On the Generation of Medical Dialogues for COVID-19. CoRR abs/2005.05442 (2020) - [i161]Yue Wu, Pan Zhou, Andrew Gordon Wilson, Eric P. Xing, Zhiting Hu:
Improving GAN Training with Probability Ratio Clipping and Sample Reweighting. CoRR abs/2006.06900 (2020) - [i160]Xingyi Yang, Nandiraju Gireesh, Eric P. Xing, Pengtao Xie:
XRayGAN: Consistency-preserving Generation of X-ray Images from Radiology Reports. CoRR abs/2006.10552 (2020) - [i159]Bowen Tan, Zichao Yang, Maruan Al-Shedivat, Eric P. Xing, Zhiting Hu:
Progressive Generation of Long Text. CoRR abs/2006.15720 (2020) - [i158]Benjamin J. Lengerich, Eric P. Xing, Rich Caruana:
On Dropout, Overfitting, and Interaction Effects in Deep Neural Networks. CoRR abs/2007.00823 (2020) - [i157]