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Jun Huan
Attentive Social Recommendation: Towards User And Item Diversities

Nov 15, 2020
Dongsheng Luo, Yuchen Bian, Xiang Zhang, Jun Huan

* 8 Pages 
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Generating Person Images with Appearance-aware Pose Stylizer

Jul 17, 2020
Siyu Huang, Haoyi Xiong, Zhi-Qi Cheng, Qingzhong Wang, Xingran Zhou, Bihan Wen, Jun Huan, Dejing Dou

* Appearing at IJCAI 2020. The code is available at https://github.com/siyuhuang/PoseStylizer 
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Parameter-Free Style Projection for Arbitrary Style Transfer

Mar 17, 2020
Siyu Huang, Haoyi Xiong, Tianyang Wang, Qingzhong Wang, Zeyu Chen, Jun Huan, Dejing Dou

* 9 pages, 12 figures 
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Ultrafast Photorealistic Style Transfer via Neural Architecture Search

Dec 05, 2019
Jie An, Haoyi Xiong, Jun Huan, Jiebo Luo


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SecureGBM: Secure Multi-Party Gradient Boosting

Nov 27, 2019
Zhi Fengy, Haoyi Xiong, Chuanyuan Song, Sijia Yang, Baoxin Zhao, Licheng Wang, Zeyu Chen, Shengwen Yang, Liping Liu, Jun Huan

* The first two authors contributed equally to the manuscript. The paper has been accepted for publication in IEEE BigData 2019 
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Towards Making Deep Transfer Learning Never Hurt

Nov 18, 2019
Ruosi Wan, Haoyi Xiong, Xingjian Li, Zhanxing Zhu, Jun Huan

* accapted as long paper at the 19th IEEE International Conference on Data Mining, 2019 
 * 10 pages 
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NormLime: A New Feature Importance Metric for Explaining Deep Neural Networks

Oct 15, 2019
Isaac Ahern, Adam Noack, Luis Guzman-Nateras, Dejing Dou, Boyang Li, Jun Huan


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Improving Adversarial Robustness via Attention and Adversarial Logit Pairing

Aug 23, 2019
Dou Goodman, Xingjian Li, Jun Huan, Tao Wei


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Fast Universal Style Transfer for Artistic and Photorealistic Rendering

Jul 06, 2019
Jie An, Haoyi Xiong, Jiebo Luo, Jun Huan, Jinwen Ma


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AGAN: Towards Automated Design of Generative Adversarial Networks

Jun 25, 2019
Hanchao Wang, Jun Huan


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The Multiplicative Noise in Stochastic Gradient Descent: Data-Dependent Regularization, Continuous and Discrete Approximation

Jun 18, 2019
Jingfeng Wu, Wenqing Hu, Haoyi Xiong, Jun Huan, Zhanxing Zhu


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StyleNAS: An Empirical Study of Neural Architecture Search to Uncover Surprisingly Fast End-to-End Universal Style Transfer Networks

Jun 06, 2019
Jie An, Haoyi Xiong, Jinwen Ma, Jiebo Luo, Jun Huan


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An Empirical Study on Regularization of Deep Neural Networks by Local Rademacher Complexity

Feb 14, 2019
Yingzhen Yang, Xingjian Li, Jun Huan

* Updated the link to the open source PaddlePaddle code of LRC Regularization 
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FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary

Feb 13, 2019
Yingzhen Yang, Nebojsa Jojic, Jun Huan


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DELTA: DEep Learning Transfer using Feature Map with Attention for Convolutional Networks

Jan 26, 2019
Xingjian Li, Haoyi Xiong, Hanchao Wang, Yuxuan Rao, Liping Liu, Jun Huan

* Accepted at ICLR 2019 
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Quasi-potential as an implicit regularizer for the loss function in the stochastic gradient descent

Jan 18, 2019
Wenqing Hu, Zhanxing Zhu, Haoyi Xiong, Jun Huan

* first and preliminary version 
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Instance-based Deep Transfer Learning

Sep 08, 2018
Tianyang Wang, Jun Huan, Michelle Zhu


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Data Dropout: Optimizing Training Data for Convolutional Neural Networks

Sep 07, 2018
Tianyang Wang, Jun Huan, Bo Li


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Discriminatory Transfer

Aug 07, 2017
Chao Lan, Jun Huan

* Presented as a poster at the 2017 Workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML 2017) 
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On the Unreported-Profile-is-Negative Assumption for Predictive Cheminformatics

Aug 07, 2017
Chao Lan, Sai Nivedita Chandrasekaran, Jun Huan

* the quality of the current version is unsatisfactory. we decide to withdraw the manuscript. thank you 
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Learning Social Circles in Ego Networks based on Multi-View Social Graphs

Dec 24, 2016
Chao Lan, Yuhao Yang, Xiaoli Li, Bo Luo, Jun Huan

* This paper has been withdrawn by the author due to its current unsatisfactory quality 
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