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Enabling the Network to Surf the Internet


Feb 24, 2021
Zhuoling Li, Haohan Wang, Tymoteusz Swistek, Weixin Chen, Yuanzheng Li, Haoqian Wang


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Active Learning to Classify Macromolecular Structures in situ for Less Supervision in Cryo-Electron Tomography


Feb 24, 2021
Xuefeng Du, Haohan Wang, Zhenxi Zhu, Xiangrui Zeng, Yi-Wei Chang, Jing Zhang, Eric Xing, Min Xu

* 14 ages 

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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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Word Shape Matters: Robust Machine Translation with Visual Embedding


Oct 20, 2020
Haohan Wang, Peiyan Zhang, 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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Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual


Aug 28, 2019
He He, Sheng Zha, Haohan Wang


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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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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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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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Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications


Aug 31, 2018
Haohan Wang, Zhenglin Wu, Eric P. Xing

* 12 pages, 5 figures 

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Deep Learning for Genomics: A Concise Overview


May 08, 2018
Tianwei Yue, Haohan Wang

* Invited chapter for Springer Book: Handbook of Deep Learning Applications 

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A Sparse Graph-Structured Lasso Mixed Model for Genetic Association with Confounding Correction


Nov 11, 2017
Wenting Ye, Xiang Liu, Haohan Wang, Eric P. Xing

* Code available at https://github.com/YeWenting/sGLMM 

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Select-Additive Learning: Improving Generalization in Multimodal Sentiment Analysis


Apr 12, 2017
Haohan Wang, Aaksha Meghawat, Louis-Philippe Morency, Eric P. Xing

* Supplementary files at: http://www.cs.cmu.edu/~haohanw/document/sal_supp.pdf 

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On the Origin of Deep Learning


Mar 03, 2017
Haohan Wang, Bhiksha Raj

* 70 pages, 200 references 

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SeDMiD for Confusion Detection: Uncovering Mind State from Time Series Brain Wave Data


Nov 29, 2016
Jingkang Yang, Haohan Wang, Jun Zhu, Eric P. Xing

* 11 pages, 2 figures, NIPS 2016 Time Series Workshop 

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Multimodal Transfer Deep Learning with Applications in Audio-Visual Recognition


Feb 18, 2016
Seungwhan Moon, Suyoun Kim, Haohan Wang

* 6 pages, MMML workshop at NIPS 2015 

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A Survey: Time Travel in Deep Learning Space: An Introduction to Deep Learning Models and How Deep Learning Models Evolved from the Initial Ideas


Nov 06, 2015
Haohan Wang, Bhiksha Raj

* 43 pages, 31 figures. Fix typos in abstract 

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Evaluating Protein-protein Interaction Predictors with a Novel 3-Dimensional Metric


Nov 06, 2015
Haohan Wang, Madhavi K. Ganapathiraju

* This article is an extended version of a poster presented in AMIA TBI 2015 

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Evaluation of Protein-protein Interaction Predictors with Noisy Partially Labeled Data Sets


Sep 18, 2015
Haohan Wang, Madhavi K. Ganapathiraju

* preprint version, 9 pages, 7 figures 

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Discovery of Important Crossroads in Road Network using Massive Taxi Trajectories


Sep 18, 2015
Ming Xu, Jianping Wu, Yiman Du, Haohan Wang, Geqi Qi, Kezhen Hu, Yunpeng Xiao


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