19 citations · 83 across the 16 of their papers we have counts for
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stat.ML2020
Pairwise Supervision Can Provably Elicit a Decision Boundary
Han Bao, Takuya Shimada, Liyuan Xu +2
Similarity learning is a general problem to elicit useful representations by predicting the relationship between a pair of patterns. This problem is related to various important pr…
stat.ML2020★ 10 cited
Calibrated Surrogate Losses for Adversarially Robust Classification
Han Bao, Clayton Scott, Masashi Sugiyama
Adversarially robust classification seeks a classifier that is insensitive to adversarial perturbations of test patterns. This problem is often formulated via a minimax objective,…
cs.LG2020★ 1 cited
Learning from Noisy Similar and Dissimilar Data
Soham Dan, Han Bao, Masashi Sugiyama
With the widespread use of machine learning for classification, it becomes increasingly important to be able to use weaker kinds of supervision for tasks in which it is hard to obt…