Stop the war!Остановите войну!
for scientists:
Google
Google Scholar
Semantic Scholar
IA Scholar
CiteSeerX
ORCIDEric P. Xing
Eric Po Xing
Person information
- affiliation: Carnegie Mellon University, School of Computer Science, Pittsburgh, PA, USA
- affiliation: Petuum Inc., Pittsburgh, PA, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2022
[j64]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)- [j63]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) - [c322]Benjamin J. Lengerich, Eric P. Xing, Rich Caruana:
Dropout as a Regularizer of Interaction Effects. AISTATS 2022: 7550-7564 - [c321]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 - [i197]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) - [i196]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) - [i195]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) - [i194]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) - [i193]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) - [i192]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) - [i191]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) - 2021
- [j62]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) - [j61]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 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
- [j60]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) - [j59]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) - [j58]Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing:
Contextual Explanation Networks. J. Mach. Learn. Res. 21: 194:1-194:44 (2020) - [j57]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) - [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 Lengerich, Eric P. Xing, Rich Caruana:
On Dropout, Overfitting, and Interaction Effects in Deep Neural Networks. CoRR abs/2007.00823 (2020) - [i157]Zeyi Huang, Haohan Wang, Eric P. Xing, Dong Huang:
Self-Challenging Improves Cross-Domain Generalization. CoRR abs/2007.02454 (2020) - [i156]Aurick Qiao, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R. Ganger, Eric P. Xing:
Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. CoRR abs/2008.12260 (2020) - [i155]Maruan Al-Shedivat, Jennifer Gillenwater, Eric P. Xing, Afshin Rostamizadeh:
Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms. CoRR abs/2010.05273 (2020) - [i154]Bowen Tan, Lianhui Qin, Eric P. Xing, Zhiting Hu:
Summarizing Text on Any Aspects: A Knowledge-Informed Weakly-Supervised Approach. CoRR abs/2010.06792 (2020) - [i153]Haohan Wang, Peiyan Zhang, Eric P. Xing:
Word Shape Matters: Robust Machine Translation with Visual Embedding. CoRR abs/2010.09997 (2020) - [i152]Xuehai He, Zhuo Cai, Wenlan Wei, Yichen Zhang, Luntian Mou, Eric P. Xing, Pengtao Xie:
Pathological Visual Question Answering. CoRR abs/2010.12435 (2020) - [i151]Hanlin Zhang, Shuai Lin, Weiyang Liu, Pan Zhou, Jian Tang, Xiaodan Liang, Eric P. Xing:
Iterative Graph Self-Distillation. CoRR abs/2010.12609 (2020) - [i150]Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing:
Squared 𝓁2 Norm as Consistency Loss for Leveraging Augmented Data to Learn Robust and Invariant Representations. CoRR abs/2011.13052 (2020) - [i149]Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Min Xu, Irina Voiculescu, Eric P. Xing:
Towards Robust Medical Image Segmentation on Small-Scale Data with Incomplete Labels. CoRR abs/2011.14164 (2020) - [i148]Benedikt Boecking, Willie Neiswanger, Eric Po Xing, Artur Dubrawski:
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling. CoRR abs/2012.06046 (2020) - [i147]Hongbo Zou, Guangjing Chen, Pengtao Xie, Sean Chen, Yongtian He, Hochih Huang, Zheng Nie, Hongbao Zhang, Tristan Bala, Kazi Tulip, Yuqi Wang, Shenlin Qin, Eric P. Xing:
Validate and Enable Machine Learning in Industrial AI. CoRR abs/2012.09610 (2020)
2010 – 2019
- 2019
- [j55]Haohan Wang, Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing:
Precision Lasso: accounting for correlations and linear dependencies in high-dimensional genomic data. Bioinform. 35(7): 1181-1187 (2019) - [j54]Haohan Wang, Tianwei Yue, Jingkang Yang, Wei Wu, Eric P. Xing:
Deep mixed model for marginal epistasis detection and population stratification correction in genome-wide association studies. BMC Bioinform. 20-S(23): 656 (2019) - [j53]Mrinmaya Sachan, Avinava Dubey, Eduard H. Hovy, Tom M. Mitchell, Dan Roth, Eric P. Xing:
Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks. Comput. Linguistics 45(4): 627-665 (2019) - [j52]Yujia Zhang, Michael Kampffmeyer, Xiaodan Liang, Dingwen Zhang, Min Tan, Eric P. Xing:
Dilated temporal relational adversarial network for generic video summarization. Multim. Tools Appl. 78(24): 35237-35261 (2019) - [j51]Michael Kampffmeyer, Nanqing Dong, Xiaodan Liang, Yujia Zhang, Eric P. Xing:
ConnNet: A Long-Range Relation-Aware Pixel-Connectivity Network for Salient Segmentation. IEEE Trans. Image Process. 28(5): 2518-2529 (2019) - [c293]Christy Y. Li, Xiaodan Liang, Zhiting Hu, Eric P. Xing:
Knowledge-Driven Encode, Retrieve, Paraphrase for Medical Image Report Generation. AAAI 2019: 6666-6673 - [c292]Haohan Wang, Da Sun, Eric P. Xing:
What if We Simply Swap the Two Text Fragments? A Straightforward yet Effective Way to Test the Robustness of Methods to Confounding Signals in Nature Language Inference Tasks. AAAI 2019: 7136-7143 - [c291]Zhiting Hu, Haoran Shi, Bowen Tan, Wentao Wang, Zichao Yang, Tiancheng Zhao, Junxian He, Lianhui Qin, Di Wang, Xuezhe Ma, Zhengzhong Liu, Xiaodan Liang, Wanrong Zhu, Devendra Singh Sachan, Eric P. Xing:
Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation. ACL (3) 2019: 159-164 - [c290]Jianheng Tang, Tiancheng Zhao, Chenyan Xiong, Xiaodan Liang, Eric P. Xing, Zhiting Hu:
Target-Guided Open-Domain Conversation. ACL (1) 2019: 5624-5634 - [c289]Baoyu Jing, Zeya Wang, Eric P. Xing:
Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-ray Reports. ACL (1) 2019: 6570-6580 - [c288]Xindi Wu, Yijun Mao, Haohan Wang, Xiangrui Zeng, Xin Gao, Eric P. Xing, Min Xu:
Regularized Adversarial Training (RAT) for Robust Cellular Electron Cryo Tomograms Classification. BIBM 2019: 1-6 - [c287]Haohan Wang, Changpeng Lu, Wei Wu, Eric P. Xing:
Graph-structured Sparse Mixed Models for Genetic Association with Confounding Factors Correction. BIBM 2019: 298-302 - [c286]Haohan Wang, Yibing Wei, Mengxin Cao, Ming Xu, Wei Wu, Eric P. Xing:
Deep Inductive Matrix Completion for Biomedical Interaction Prediction. BIBM 2019: 520-527 - [c285]Michael Kampffmeyer, Yinbo Chen, Xiaodan Liang, Hao Wang, Yujia Zhang, Eric P. Xing:
Rethinking Knowledge Graph Propagation for Zero-Shot Learning. CVPR 2019: 11487-11496 - [c284]Jinliang Wei, Garth A. Gibson, Phillip B. Gibbons, Eric P. Xing:
Automating Dependence-Aware Parallelization of Machine Learning Training on Distributed Shared Memory. EuroSys 2019: 42:1-42:17 - [c283]Wei Dai, Yi Zhou, Nanqing Dong, Hao Zhang, Eric P. Xing:
Toward Understanding the Impact of Staleness in Distributed Machine Learning. ICLR (Poster) 2019 - [c282]Bowen Tan, Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric P. Xing:
Connecting the Dots Between MLE and RL for Sequence Generation. DeepRLStructPred@ICLR 2019 - [c281]Haohan Wang, Zexue He, Zachary C. Lipton, Eric P. Xing:
Learning Robust Representations by Projecting Superficial Statistics Out. ICLR 2019 - [c280]Haowen Xu, Hao Zhang, Zhiting Hu, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing:
AutoLoss: Learning Discrete Schedule for Alternate Optimization. ICLR (Poster) 2019 - [c279]Aurick Qiao, Bryon Aragam, Bingjing Zhang, Eric P. Xing:
Fault Tolerance in Iterative-Convergent Machine Learning. ICML 2019: 5220-5230 - [c278]Hongyang Zhang, Yaodong Yu, Jiantao Jiao, Eric P. Xing, Laurent El Ghaoui, Michael I. Jordan:
Theoretically Principled Trade-off between Robustness and Accuracy. ICML 2019: 7472-7482 - [c277]Zeya Wang, Nanqing Dong, Sean D. Rosario, Min Xu, Pengtao Xie, Eric P. Xing:
Ellipse Detection of Optic Disc-and-Cup Boundary in Fundus Images. ISBI 2019: 601-604 - [c276]Nanqing Dong, Min Xu, Xiaodan Liang, Yiliang Jiang, Wei Dai, Eric P. Xing:
Neural Architecture Search for Adversarial Medical Image Segmentation. MICCAI (6) 2019: 828-836 - [c275]Keyang Xu, Mike Lam, Jingzhi Pang, Xin Gao, Charlotte Band, Piyush Mathur, Frank Papay, Ashish K. Khanna, Jacek B. Cywinski, Kamal Maheshwari, Pengtao Xie, Eric P. Xing:
Multimodal Machine Learning for Automated ICD Coding. MLHC 2019: 197-215 - [c274]Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing:
Learning Sample-Specific Models with Low-Rank Personalized Regression. NeurIPS 2019: 3570-3580 - [c273]Haohan Wang, Songwei Ge, Zachary C. Lipton, Eric P. Xing:
Learning Robust Global Representations by Penalizing Local Predictive Power. NeurIPS 2019: 10506-10518 - [c272]Biwei Huang, Kun Zhang, Pengtao Xie, Mingming Gong, Eric P. Xing, Clark Glymour:
Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering. NeurIPS 2019: 13510-13521 - [c271]Zhiting Hu, Bowen Tan, Ruslan Salakhutdinov, Tom M. Mitchell, Eric P. Xing:
Learning Data Manipulation for Augmentation and Weighting. NeurIPS 2019: 15738-15749 - [c270]Haohan Wang,