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Tue 7:00 Searching to Exploit Memorization Effect in Learning with Noisy Labels
QUANMING YAO · Hansi Yang · Bo Han · Gang Niu · James Kwok
Tue 7:00 Minimax Rate for Learning From Pairwise Comparisons in the BTL Model
Julien Hendrickx · Alex Olshevsky · Venkatesh Saligrama
Tue 7:00 Training Binary Neural Networks through Learning with Noisy Supervision
Kai Han · Yunhe Wang · Yixing Xu · Chunjing Xu · Enhua Wu · Chang Xu
Tue 7:00 Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case
shuai zhang · Meng Wang · Sijia Liu · Pin-Yu Chen · Jinjun Xiong
Tue 7:00 Confidence-Aware Learning for Deep Neural Networks
Jooyoung Moon · Jihyo Kim · Younghak Shin · Sangheum Hwang
Tue 7:00 Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling
Will Grathwohl · Kuan-Chieh Wang · Joern-Henrik Jacobsen · David Duvenaud · Richard Zemel
Tue 7:00 Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting
Niccolo Dalmasso · Rafael Izbicki · Ann Lee
Tue 7:00 Layered Sampling for Robust Optimization Problems
Hu Ding · Zixiu Wang
Tue 7:00 On Variational Learning of Controllable Representations for Text without Supervision
Peng Xu · Jackie Chi Kit Cheung · Yanshuai Cao
Tue 7:00 Mutual Transfer Learning for Massive Data
Ching-Wei Cheng · Xingye Qiao · Guang Cheng
Tue 7:00 A Simple Framework for Contrastive Learning of Visual Representations
Ting Chen · Simon Kornblith · Mohammad Norouzi · Geoffrey Hinton
Tue 7:00 NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Tony Duan · Anand Avati · Daisy Ding · Khanh K. Thai · Sanjay Basu · Andrew Ng · Alejandro Schuler