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Self-Challenging Improves Cross-Domain Generalization

Jul 05, 2020
Zeyi Huang, Haohan Wang, Eric P. Xing, Dong Huang

* to appear at ECCV2020 as an oral paper 

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On Dropout, Overfitting, and Interaction Effects in Deep Neural Networks

Jul 02, 2020
Benjamin Lengerich, Eric P. Xing, Rich Caruana


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Improving GAN Training with Probability Ratio Clipping and Sample Reweighting

Jun 30, 2020
Yue Wu, Pan Zhou, Andrew Gordon Wilson, Eric P. Xing, Zhiting Hu

* Fixed typos. Code available at: https://github.com/Holmeswww/PPOGAN 

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Progressive Generation of Long Text

Jun 28, 2020
Bowen Tan, Zichao Yang, Maruan AI-Shedivat, Eric P. Xing, Zhiting Hu

* Code available at https://github.com/tanyuqian/progressive-generation 

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Distributed, partially collapsed MCMC for Bayesian Nonparametrics

Jan 15, 2020
Avinava Dubey, Michael Minyi Zhang, Eric P. Xing, Sinead A. Williamson

* Accepted in AISTATS 2020 

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Learning Data Manipulation for Augmentation and Weighting

Oct 28, 2019
Zhiting Hu, Bowen Tan, Ruslan Salakhutdinov, Tom Mitchell, Eric P. Xing

* NeurIPS 2019 

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Learning Sample-Specific Models with Low-Rank Personalized Regression

Oct 15, 2019
Benjamin Lengerich, Bryon Aragam, Eric P. Xing

* Accepted at NeurIPS 2019 

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Learning Sparse Nonparametric DAGs

Sep 29, 2019
Xun Zheng, Chen Dan, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

* 17 pages, 5 figures 

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ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations

Aug 05, 2019
Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy, Willie Neiswanger, Barnabas Poczos, Jeff Schneider, Eric P. Xing


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Target-Guided Open-Domain Conversation

May 29, 2019
Jianheng Tang, Tiancheng Zhao, Chenyan Xiong, Xiaodan Liang, Eric P. Xing, Zhiting Hu

* ACL 2019. Data and code available at https://github.com/squareRoot3/Target-Guided-Conversation. fixed typos 

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Learning Robust Global Representations by Penalizing Local Predictive Power

May 29, 2019
Haohan Wang, Songwei Ge, Eric P. Xing, Zachary C. Lipton


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High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks

May 28, 2019
Haohan Wang, Xindi Wu, Pengcheng Yin, Eric P. Xing


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Adversarial Domain Adaptation Being Aware of Class Relationships

May 28, 2019
Zeya Wang, Baoyu Jing, Yang Ni, Nanqing Dong, Pengtao Xie, Eric P. Xing


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Knowledge-driven Encode, Retrieve, Paraphrase for Medical Image Report Generation

Mar 25, 2019
Christy Y. Li, Xiaodan Liang, Zhiting Hu, Eric P. Xing


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Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly

Mar 15, 2019
Kirthevasan Kandasamy, Karun Raju Vysyaraju, Willie Neiswanger, Biswajit Paria, Christopher R. Collins, Jeff Schneider, Barnabas Poczos, Eric P. Xing


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Learning Robust Representations by Projecting Superficial Statistics Out

Mar 02, 2019
Haohan Wang, Zexue He, Zachary C. Lipton, Eric P. Xing

* To appear at ICLR 2019. Implementation: https://github.com/HaohanWang/HEX 

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Theoretically Principled Trade-off between Robustness and Accuracy

Jan 24, 2019
Hongyang Zhang, Yaodong Yu, Jiantao Jiao, Eric P. Xing, Laurent El Ghaoui, Michael I. Jordan

* Technical details of the winning entry to the NeurIPS 2018 Adversarial Vision Challenge 

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Stackelberg GAN: Towards Provable Minimax Equilibrium via Multi-Generator Architectures

Nov 19, 2018
Hongyang Zhang, Susu Xu, Jiantao Jiao, Pengtao Xie, Ruslan Salakhutdinov, Eric P. Xing

* 27 pages, 13 figures, 6 tables 

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Discourse in Multimedia: A Case Study in Information Extraction

Nov 13, 2018
Mrinmaya Sachan, Kumar Avinava Dubey, Eduard H. Hovy, Tom M. Mitchell, Dan Roth, Eric P. Xing


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DAGs with NO TEARS: Continuous Optimization for Structure Learning

Nov 03, 2018
Xun Zheng, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

* 22 pages, 8 figures, accepted to NIPS 2018 

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Transformation Autoregressive Networks

Oct 23, 2018
Junier B. Oliva, Avinava Dubey, Manzil Zaheer, Barnabás Póczos, Ruslan Salakhutdinov, Eric P. Xing, Jeff Schneider

* ICML 2018 

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Fault Tolerance in Iterative-Convergent Machine Learning

Oct 17, 2018
Aurick Qiao, Bryon Aragam, Bingjing Zhang, Eric P. Xing


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Toward Understanding the Impact of Staleness in Distributed Machine Learning

Oct 08, 2018
Wei Dai, Yi Zhou, Nanqing Dong, Hao Zhang, Eric P. Xing

* 19 pages, 12 figures 

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DiCE: The Infinitely Differentiable Monte-Carlo Estimator

Sep 19, 2018
Jakob Foerster, Gregory Farquhar, Maruan Al-Shedivat, Tim Rocktäschel, Eric P. Xing, Shimon Whiteson


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Toward Controlled Generation of Text

Sep 13, 2018
Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing

* Code adapted for text style transfer is released at: https://github.com/asyml/texar/tree/master/examples/text_style_transfer 

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Sample Complexity of Nonparametric Semi-Supervised Learning

Sep 10, 2018
Chen Dan, Liu Leqi, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

* 18 pages, 3 figures 

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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

Sep 07, 2018
Haohan Wang, Da Sun, Eric P. Xing

* 8 pages 

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Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation

Sep 04, 2018
Zhiting Hu, Haoran Shi, Zichao Yang, Bowen Tan, Tiancheng Zhao, Junxian He, Wentao Wang, Xingjiang Yu, Lianhui Qin, Di Wang, Xuezhe Ma, Hector Liu, Xiaodan Liang, Wanrong Zhu, Devendra Singh Sachan, Eric P. Xing

* 14 pages; Github: https://github.com/asyml/texar 

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