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Poster
Tue 7:00 Laplacian Regularized Few-Shot Learning
Imtiaz Ziko · Jose Dolz · Eric Granger · Ismail Ben Ayed
Poster
Tue 7:00 Training Binary Neural Networks through Learning with Noisy Supervision
Kai Han · Yunhe Wang · Yixing Xu · Chunjing Xu · Enhua Wu · Chang Xu
Poster
Tue 7:00 Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data
Lan-Zhe Guo · Zhen-Yu Zhang · Yuan Jiang · Yufeng Li · Zhi-Hua Zhou
Poster
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
Poster
Tue 7:00 A Simple Framework for Contrastive Learning of Visual Representations
Ting Chen · Simon Kornblith · Mohammad Norouzi · Geoffrey Hinton
Poster
Tue 7:00 Faster Graph Embeddings via Coarsening
Matthew Fahrbach · Gramoz Goranci · Richard Peng · Sushant Sachdeva · Chi Wang
Poster
Tue 7:00 Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms
Chaosheng Dong · Bo Zeng
Poster
Tue 7:00 Individual Fairness for k-Clustering
Sepideh Mahabadi · Ali Vakilian
Poster
Tue 7:00 Learning with Multiple Complementary Labels
LEI FENG · Takuo Kaneko · Bo Han · Gang Niu · Bo An · Masashi Sugiyama
Poster
Tue 7:00 Layered Sampling for Robust Optimization Problems
Hu Ding · Zixiu Wang
Poster
Tue 7:00 Searching to Exploit Memorization Effect in Learning with Noisy Labels
QUANMING YAO · Hansi Yang · Bo Han · Gang Niu · James Kwok
Poster
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