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Unsupervised Paraphrase Generation via Dynamic Blocking

Oct 24, 2020
Tong Niu, Semih Yavuz, Yingbo Zhou, Huan Wang, Nitish Shirish Keskar, Caiming Xiong

* 10 pages 

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How Important is the Train-Validation Split in Meta-Learning?

Oct 12, 2020
Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason D. Lee, Sham Kakade, Huan Wang, Caiming Xiong


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Towards Understanding Hierarchical Learning: Benefits of Neural Representations

Jun 24, 2020
Minshuo Chen, Yu Bai, Jason D. Lee, Tuo Zhao, Huan Wang, Caiming Xiong, Richard Socher


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Collaborative Distillation for Ultra-Resolution Universal Style Transfer

Mar 24, 2020
Huan Wang, Yijun Li, Yuehai Wang, Haoji Hu, Ming-Hsuan Yang

* Accepted by CVPR 2020, higher-resolution images than the camera-ready version 

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MNN: A Universal and Efficient Inference Engine

Feb 27, 2020
Xiaotang Jiang, Huan Wang, Yiliu Chen, Ziqi Wu, Lichuan Wang, Bin Zou, Yafeng Yang, Zongyang Cui, Yu Cai, Tianhang Yu, Chengfei Lv, Zhihua Wu

* Accepted by MLSys 2020 

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Taylorized Training: Towards Better Approximation of Neural Network Training at Finite Width

Feb 24, 2020
Yu Bai, Ben Krause, Huan Wang, Caiming Xiong, Richard Socher


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Neural Bayes: A Generic Parameterization Method for Unsupervised Representation Learning

Feb 20, 2020
Devansh Arpit, Huan Wang, Caiming Xiong, Richard Socher, Yoshua Bengio


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Opposite Structure Learning for Semi-supervised Domain Adaptation

Feb 06, 2020
Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, Yun Fu

* 8 pages without citations 

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Attentive Student Meets Multi-Task Teacher: Improved Knowledge Distillation for Pretrained Models

Nov 09, 2019
Linqing Liu, Huan Wang, Jimmy Lin, Richard Socher, Caiming Xiong


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Global Capacity Measures for Deep ReLU Networks via Path Sampling

Oct 22, 2019
Ryan Theisen, Jason M. Klusowski, Huan Wang, Nitish Shirish Keskar, Caiming Xiong, Richard Socher


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On the Generalization Gap in Reparameterizable Reinforcement Learning

May 29, 2019
Huan Wang, Stephan Zheng, Caiming Xiong, Richard Socher

* Proceedings of the 36 th International Conference on Machine Learning, Long Beach, California, PMLR 97, 2019 

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Triplet Distillation for Deep Face Recognition

May 19, 2019
Yushu Feng, Huan Wang, Daniel T. Yi, Roland Hu

* 5 pages, 2 tables, accpeted by ICML 2019 ODML-CDNNR Workshop 

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Structured Pruning for Efficient ConvNets via Incremental Regularization

Nov 20, 2018
Huan Wang, Qiming Zhang, Yuehai Wang, Haoji Hu

* Accepted by NIPS 2018 workshop on "Compact Deep Neural Network Representation with Industrial Applications" 

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Three Dimensional Convolutional Neural Network Pruning with Regularization-Based Method

Nov 19, 2018
Yuxin Zhang, Huan Wang, Yang Luo, Roland Hu

* Accepted by NIPS 2018 Workshop CDNNRIA 

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Identifying Generalization Properties in Neural Networks

Sep 19, 2018
Huan Wang, Nitish Shirish Keskar, Caiming Xiong, Richard Socher

* 23 pages 

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Structured Probabilistic Pruning for Convolutional Neural Network Acceleration

Sep 10, 2018
Huan Wang, Qiming Zhang, Yuehai Wang, Haoji Hu

* Proceedings of the British Machine Vision Conference (BMVC), 2018 
* CNN model acceleration, 13 pages, 6 figures, accepted by Proceedings of the British Machine Vision Conference (BMVC), 2018 oral 

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Structured Deep Neural Network Pruning by Varying Regularization Parameters

Apr 25, 2018
Huan Wang, Qiming Zhang, Yuehai Wang, Roland Hu

* 7 pages, 3 figures 

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Exploiting Color Name Space for Salient Object Detection

Mar 27, 2017
Jing Lou, Huan Wang, Longtao Chen, Qingyuan Xia, Wei Zhu, Mingwu Ren

* 13 pages, 10 figures, 2 tables 

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Synthesizing Training Images for Boosting Human 3D Pose Estimation

Jan 05, 2017
Wenzheng Chen, Huan Wang, Yangyan Li, Hao Su, Zhenhua Wang, Changhe Tu, Dani Lischinski, Daniel Cohen-Or, Baoquan Chen


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A Batchwise Monotone Algorithm for Dictionary Learning

Jan 31, 2015
Huan Wang, John Wright, Daniel Spielman


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Exact Recovery of Sparsely-Used Dictionaries

Jun 26, 2012
Daniel A. Spielman, Huan Wang, John Wright


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On the Local Correctness of L^1 Minimization for Dictionary Learning

Jan 29, 2011
Quan Geng, Huan Wang, John Wright

* 37 pages, 1 figure 

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