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A Data-Centric Framework for Composable NLP Workflows


Mar 03, 2021
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

* 8 pages, 4 figures, EMNLP 2020 

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Technology Readiness Levels for Machine Learning Systems


Jan 11, 2021
Alexander Lavin, Ciarán M. Gilligan-Lee, Alessya Visnjic, Siddha Ganju, Dava Newman, Sujoy Ganguly, Danny Lange, Atılım Güneş Baydin, Amit Sharma, Adam Gibson, Yarin Gal, Eric P. Xing, Chris Mattmann, James Parr


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Towards Robust Medical Image Segmentation on Small-Scale Data with Incomplete Labels


Nov 28, 2020
Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Min Xu, Irina Voiculescu, Eric P. Xing


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Squared $\ell_2$ Norm as Consistency Loss for Leveraging Augmented Data to Learn Robust and Invariant Representations


Nov 25, 2020
Haohan Wang, Zeyi Huang, Xindi Wu, Eric P. Xing

* 12 pages and an additional 9 pages as appendix 

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Iterative Graph Self-Distillation


Oct 23, 2020
Hanlin Zhang, Shuai Lin, Weiyang Liu, Pan Zhou, Jian Tang, Xiaodan Liang, Eric P. Xing


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Word Shape Matters: Robust Machine Translation with Visual Embedding


Oct 20, 2020
Haohan Wang, Peiyan Zhang, Eric P. Xing


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Summarizing Text on Any Aspects: A Knowledge-Informed Weakly-Supervised Approach


Oct 18, 2020
Bowen Tan, Lianhui Qin, Eric P. Xing, Zhiting Hu

* EMNLP 2020, code and data available at https://github.com/tanyuqian/aspect-based-summarization 

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Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning


Aug 27, 2020
Aurick Qiao, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R. Ganger, Eric P. Xing


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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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