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Learning Curves for Analysis of Deep Networks

Oct 21, 2020
Derek Hoiem, Tanmay Gupta, Zhizhong Li, Michal M. Shlapentokh-Rothman


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Regularizing Reasons for Outfit Evaluation with Gradient Penalty

Feb 02, 2020
Xingxing Zou, Zhizhong Li, Ke Bai, Dahua Lin, Waikeung Wong

* 10 pages 

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Dreaming to Distill: Data-free Knowledge Transfer via DeepInversion

Dec 18, 2019
Hongxu Yin, Pavlo Molchanov, Zhizhong Li, Jose M. Alvarez, Arun Mallya, Derek Hoiem, Niraj K. Jha, Jan Kautz


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Policy Continuation with Hindsight Inverse Dynamics

Nov 01, 2019
Hao Sun, Zhizhong Li, Xiaotong Liu, Dahua Lin, Bolei Zhou


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Biased Estimates of Advantages over Path Ensembles

Sep 15, 2019
Lanxin Lei, Zhizhong Li, Dahua Lin


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Anchor Tasks: Inexpensive, Shared, and Aligned Tasks for Domain Adaptation

Aug 16, 2019
Zhizhong Li, Linjie Luo, Sergey Tulyakov, Qieyun Dai, Derek Hoiem


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$\mathcal{G}$-Distillation: Reducing Overconfident Errors on Novel Samples

Apr 09, 2018
Zhizhong Li, Derek Hoiem

* Paper under review as an anonymous submission 

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Deep Nearest Class Mean Model for Incremental Odor Classification

Jan 08, 2018
Yu Cheng, Angus Wong, Kevin Hung, Zhizhong Li, Weitong Li

* 15 pages, 6 figures 

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Complete 3D Scene Parsing from Single RGBD Image

Oct 25, 2017
Chuhang Zou, Zhizhong Li, Derek Hoiem


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Integrating Specialized Classifiers Based on Continuous Time Markov Chain

Sep 07, 2017
Zhizhong Li, Dahua Lin

* Published at IJCAI-17, typo fixed 

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PolyNet: A Pursuit of Structural Diversity in Very Deep Networks

Jul 17, 2017
Xingcheng Zhang, Zhizhong Li, Chen Change Loy, Dahua Lin

* Tech report 

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Learning without Forgetting

Feb 14, 2017
Zhizhong Li, Derek Hoiem

* Conference version appears in ECCV 2016; updated with journal version 

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