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The 2021 schedule is still incomplete
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Oral
Thu Jul 22 09:00 PM -- 09:20 PM (KST)
Confidence Scores Make Instance-dependent Label-noise Learning Possible
In Semisupervised Learning 1
Antonin Berthon · Bo Han · Gang Niu · Tongliang Liu · Masashi Sugiyama
[ Paper ]
Spotlight
Thu Jul 22 09:20 PM -- 09:25 PM (KST)
Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation
In Semisupervised Learning 1
Masahiro Kato · Takeshi Teshima
[ Paper ]
Spotlight
Thu Jul 22 09:25 PM -- 09:30 PM (KST)
Self-Damaging Contrastive Learning
In Semisupervised Learning 1
Ziyu Jiang · Tianlong Chen · Bobak Mortazavi · Zhangyang “Atlas” Wang
[ Paper ]
Spotlight
Thu Jul 22 09:30 PM -- 09:35 PM (KST)
Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels
In Semisupervised Learning 1
Songhua Wu · Xiaobo Xia · Tongliang Liu · Bo Han · Mingming Gong · Nannan Wang · Haifeng Liu · Gang Niu
[ Paper ]
Spotlight
Thu Jul 22 09:35 PM -- 09:40 PM (KST)
GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings
In Semisupervised Learning 1
Matthias Fey · Jan Eric Lenssen · Frank Weichert · Jure Leskovec
[ Paper ]
Spotlight
Thu Jul 22 09:40 PM -- 09:45 PM (KST)
Neural Transformation Learning for Deep Anomaly Detection Beyond Images
In Semisupervised Learning 1
Chen Qiu · Timo Pfrommer · Marius Kloft · Stephan Mandt · Maja Rudolph
[ Paper ]
Spotlight
Thu Jul 22 09:45 PM -- 09:50 PM (KST)
Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data
In Semisupervised Learning 1
Sung Woo Park · Junseok Kwon
[ Paper ]
Q&A
Thu Jul 22 09:50 PM -- 09:55 PM (KST)
Q&A
In Semisupervised Learning 1