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23 Results
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Poster
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Mon 17:00 |
When Optimizing -Divergence is Robust with Label Noise Jiaheng Wei · Yang Liu |
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Poster
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Mon 17:00 |
Robust Curriculum Learning: from clean label detection to noisy label self-correction Tianyi Zhou · Shengjie Wang · Jeff Bilmes |
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Spotlight
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Tue 4:48 |
Noise against noise: stochastic label noise helps combat inherent label noise Pengfei Chen · Guangyong Chen · Junjie Ye · jingwei zhao · Pheng-Ann Heng |
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Poster
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Mon 1:00 |
Noise against noise: stochastic label noise helps combat inherent label noise Pengfei Chen · Guangyong Chen · Junjie Ye · jingwei zhao · Pheng-Ann Heng |
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Poster
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Tue 1:00 |
Policy-Driven Attack: Learning to Query for Hard-label Black-box Adversarial Examples Ziang Yan · Yiwen Guo · Jian Liang · Changshui Zhang |
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Poster
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Thu 9:00 |
Robust early-learning: Hindering the memorization of noisy labels Xiaobo Xia · Tongliang Liu · Bo Han · Chen Gong · Nannan Wang · Zongyuan Ge · Yi Chang |
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Spotlight
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Thu 20:25 |
Learning with Feature-Dependent Label Noise: A Progressive Approach Yikai Zhang · Songzhu Zheng · Pengxiang Wu · Mayank Goswami · Chao Chen |
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Poster
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Wed 17:00 |
Learning with Feature-Dependent Label Noise: A Progressive Approach Yikai Zhang · Songzhu Zheng · Pengxiang Wu · Mayank Goswami · Chao Chen |
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Poster
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Wed 17:00 |
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach Hao Cheng · Zhaowei Zhu · Xingyu Li · Yifei Gong · Xing Sun · Yang Liu |
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Workshop
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Fri 14:01 |
Contributed Talk 3 - Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks Curtis G Northcutt |
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Poster
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Mon 17:00 |
Tilted Empirical Risk Minimization Tian Li · Ahmad Beirami · Maziar Sanjabi · Virginia Smith |
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Poster
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Tue 1:00 |
Capturing Label Characteristics in VAEs Tom Joy · Sebastian Schmon · Philip Torr · Siddharth N · Tom Rainforth |