Jun Huan

Attentive Social Recommendation: Towards User And Item Diversities

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

* 8 Pages

Access Paper or Ask Questions

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

Access Paper or Ask Questions

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

Access Paper or Ask Questions

Ultrafast Photorealistic Style Transfer via Neural Architecture Search

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

Access Paper or Ask Questions

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

Access Paper or Ask Questions

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

Access Paper or Ask Questions

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

Access Paper or Ask Questions

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

Access Paper or Ask Questions

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

Access Paper or Ask Questions

FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary

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

Access Paper or Ask Questions

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

Access Paper or Ask Questions

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

Access Paper or Ask Questions

Instance-based Deep Transfer Learning

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

Access Paper or Ask Questions

Data Dropout: Optimizing Training Data for Convolutional Neural Networks

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

Access Paper or Ask Questions

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)

Access Paper or Ask Questions

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

Access Paper or Ask Questions

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

Access Paper or Ask Questions

Jun Huan

Attentive Social Recommendation: Towards User And Item Diversities

Generating Person Images with Appearance-aware Pose Stylizer

Parameter-Free Style Projection for Arbitrary Style Transfer

Ultrafast Photorealistic Style Transfer via Neural Architecture Search

SecureGBM: Secure Multi-Party Gradient Boosting

Towards Making Deep Transfer Learning Never Hurt

NormLime: A New Feature Importance Metric for Explaining Deep Neural Networks

Improving Adversarial Robustness via Attention and Adversarial Logit Pairing

Fast Universal Style Transfer for Artistic and Photorealistic Rendering

AGAN: Towards Automated Design of Generative Adversarial Networks

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

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

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

FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary

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

Quasi-potential as an implicit regularizer for the loss function in the stochastic gradient descent

Instance-based Deep Transfer Learning

Data Dropout: Optimizing Training Data for Convolutional Neural Networks

Discriminatory Transfer

On the Unreported-Profile-is-Negative Assumption for Predictive Cheminformatics

Learning Social Circles in Ego Networks based on Multi-View Social Graphs