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Once Quantized for All: Progressively Searching for Quantized Efficient Models

Oct 09, 2020
Mingzhu Shen, Feng Liang, Chuming Li, Chen Lin, Ming Sun, Junjie Yan, Wanli Ouyang

* The first two authors contributed equally 

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Computation Reallocation for Object Detection

Dec 24, 2019
Feng Liang, Chen Lin, Ronghao Guo, Ming Sun, Wei Wu, Junjie Yan, Wanli Ouyang

* ICLR2020 

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Improved Hybrid Layered Image Compression using Deep Learning and Traditional Codecs

Jul 15, 2019
Haisheng Fu, Feng Liang, Bo Lei, Nai Bian, Qian zhang, Mohammad Akbari, Jie Liang, Chengjie Tu

* Submitted to Signal Processing: Image Communication 

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A Deep Image Compression Framework for Face Recognition

Jul 03, 2019
Nai Bian, Feng Liang, Haisheng Fu, Bo Lei

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Bayesian Regularization for Graphical Models with Unequal Shrinkage

May 20, 2018
Lingrui Gan, Naveen N. Narisetty, Feng Liang

* To appear in Journal of the American Statistical Association (Theory & Methods) 

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Discriminative Similarity for Clustering and Semi-Supervised Learning

Sep 05, 2017
Yingzhen Yang, Feng Liang, Nebojsa Jojic, Shuicheng Yan, Jiashi Feng, Thomas S. Huang

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An Empirical Bayes Approach for High Dimensional Classification

Feb 16, 2017
Yunbo Ouyang, Feng Liang

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Clustering With Side Information: From a Probabilistic Model to a Deterministic Algorithm

Oct 31, 2015
Daniel Khashabi, John Wieting, Jeffrey Yufei Liu, Feng Liang

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PAC-Bayesian AUC classification and scoring

Oct 13, 2014
James Ridgway, Pierre Alquier, Nicolas Chopin, Feng Liang

* Accepted at NIPS 2014 

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Heteroscedastic Relevance Vector Machine

Jan 10, 2013
Daniel Khashabi, Mojtaba Ziyadi, Feng Liang

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