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Eric Xing
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling

Dec 11, 2020
Benedikt Boecking, Willie Neiswanger, Eric Xing, Artur Dubrawski


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Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms

Oct 11, 2020
Maruan Al-Shedivat, Jennifer Gillenwater, Eric Xing, Afshin Rostamizadeh

* 27 pages, 7 figures 
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Pathological Visual Question Answering

Oct 06, 2020
Xuehai He, Zhuo Cai, Wenlan Wei, Yichen Zhang, Luntian Mou, Eric Xing, Pengtao Xie

* arXiv admin note: text overlap with arXiv:2003.10286 
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XRayGAN: Consistency-preserving Generation of X-ray Images from Radiology Reports

Jun 17, 2020
Xingyi Yang, Nandiraju Gireesh, Eric Xing, Pengtao Xie


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On the Generation of Medical Dialogues for COVID-19

May 11, 2020
Wenmian Yang, Guangtao Zeng, Bowen Tan, Zeqian Ju, Subrato Chakravorty, Xuehai He, Shu Chen, Xingyi Yang, Qingyang Wu, Zhou Yu, Eric Xing, Pengtao Xie


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Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-Ray Reports

Apr 26, 2020
Baoyu Jing, Zeya Wang, Eric Xing

* ACL 2019 
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Learning from Imperfect Annotations

Apr 07, 2020
Emmanouil Antonios Platanios, Maruan Al-Shedivat, Eric Xing, Tom Mitchell


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PathVQA: 30000+ Questions for Medical Visual Question Answering

Mar 07, 2020
Xuehai He, Yichen Zhang, Luntian Mou, Eric Xing, Pengtao Xie


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Generalized Zero-shot ICD Coding

Sep 28, 2019
Congzheng Song, Shanghang Zhang, Najmeh Sadoughi, Pengtao Xie, Eric Xing


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Efficient Exploration via State Marginal Matching

Jun 12, 2019
Lisa Lee, Benjamin Eysenbach, Emilio Parisotto, Eric Xing, Sergey Levine, Ruslan Salakhutdinov

* Videos and code: https://sites.google.com/view/state-marginal-matching 
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Regularizing Black-box Models for Improved Interpretability (HILL 2019 Version)

May 31, 2019
Gregory Plumb, Maruan Al-Shedivat, Eric Xing, Ameet Talwalkar

* presented at 2019 ICML Workshop on Human in the Loop Learning (HILL 2019), Long Beach, USA. arXiv admin note: substantial text overlap with arXiv:1902.06787 
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SysML: The New Frontier of Machine Learning Systems

May 01, 2019
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Jennifer Chayes, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim Hazelwood, Furong Huang, Martin Jaggi, Kevin Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konečný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Aparna Lakshmiratan, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Murray, Kunle Olukotun, Dimitris Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar


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Explaining a black-box using Deep Variational Information Bottleneck Approach

Feb 19, 2019
Seojin Bang, Pengtao Xie, Wei Wu, Eric Xing


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Regularizing Black-box Models for Improved Interpretability

Feb 18, 2019
Gregory Plumb, Maruan Al-Shedivat, Eric Xing, Ameet Talwalkar


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Toward Unsupervised Text Content Manipulation

Feb 08, 2019
Wentao Wang, Zhiting Hu, Zichao Yang, Haoran Shi, Frank Xu, Eric Xing

* The first 2 authors contributed equally. Dataset is released at https://github.com/ZhitingHu/text_content_manipulation 
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ProBO: a Framework for Using Probabilistic Programming in Bayesian Optimization

Jan 31, 2019
Willie Neiswanger, Kirthevasan Kandasamy, Barnabas Poczos, Jeff Schneider, Eric Xing


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Text Infilling

Jan 18, 2019
Wanrong Zhu, Zhiting Hu, Eric Xing


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Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Records

Nov 26, 2018
Xiangan Liu, Keyang Xu, Pengtao Xie, Eric Xing

* Machine Learning for Health (ML4H) Workshop at NeurIPS 2018 arXiv:1811.07216 
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Connecting the Dots Between MLE and RL for Sequence Generation

Nov 24, 2018
Bowen Tan, Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric Xing

* The first two authors contributed equally. Code available at: https://github.com/asyml/texar/tree/master/examples/seq2seq_exposure_bias 
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On the Complexity of Exploration in Goal-Driven Navigation

Nov 16, 2018
Maruan Al-Shedivat, Lisa Lee, Ruslan Salakhutdinov, Eric Xing

* Relational Representation Learning Workshop (NIPS 2018) 
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Multimodal Machine Learning for Automated ICD Coding

Oct 31, 2018
Keyang Xu, Mike Lam, Jingzhi Pang, Xin Gao, Charlotte Band, Piyush Mathur MD, Frank Papay MD, Ashish K. Khanna MD, Jacek B. Cywinski MD, Kamal Maheshwari MD, Pengtao Xie, Eric Xing


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Real-to-Virtual Domain Unification for End-to-End Autonomous Driving

Sep 06, 2018
Luona Yang, Xiaodan Liang, Tairui Wang, Eric Xing


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Missing Value Imputation Based on Deep Generative Models

Aug 05, 2018
Hongbao Zhang, Pengtao Xie, Eric Xing


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On the Automatic Generation of Medical Imaging Reports

Jul 20, 2018
Baoyu Jing, Pengtao Xie, Eric Xing

* ACL 2018 
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Geometric Generalization Based Zero-Shot Learning Dataset Infinite World: Simple Yet Powerful

Jul 11, 2018
Rajesh Chidambaram, Michael Kampffmeyer, Willie Neiswanger, Xiaodan Liang, Thomas Lachmann, Eric Xing

* ICML 2018, Workshop TADGM 
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CIRL: Controllable Imitative Reinforcement Learning for Vision-based Self-driving

Jul 10, 2018
Xiaodan Liang, Tairui Wang, Luona Yang, Eric Xing

* To appear in ECCV 2018 
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Deep Generative Models with Learnable Knowledge Constraints

Jun 26, 2018
Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Xiaodan Liang, Lianhui Qin, Haoye Dong, Eric Xing


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Gated Path Planning Networks

Jun 17, 2018
Lisa Lee, Emilio Parisotto, Devendra Singh Chaplot, Eric Xing, Ruslan Salakhutdinov

* ICML 2018 
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