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20212023
most citedIdentifiability of Label Noise Transition Matrix

6 citations · 14 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023

Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors

Zeyu Tang, Yatong Chen, Yang Liu +1

The pursuit of long-term fairness involves the interplay between decision-making and the underlying data generating process. In this paper, through causal modeling with a directed…

cs.LG2022★ 6 cited

Identifiability of Label Noise Transition Matrix

Yang Liu, Hao Cheng, Kun Zhang

The noise transition matrix plays a central role in the problem of learning with noisy labels. Among many other reasons, a large number of existing solutions rely on access to it.…

cs.LG2021★ 3 cited

Model Transferability With Responsive Decision Subjects

Yatong Chen, Zeyu Tang, Kun Zhang +1

Given an algorithmic predictor that is accurate on some source population consisting of strategic human decision subjects, will it remain accurate if the population respond to it?…

cs.CV2021

Region-Aware Network: Model Human's Top-Down Visual Perception Mechanism for Crowd Counting

Yuehai Chen, Jing Yang, Dong Zhang +3

Background noise and scale variation are common problems that have been long recognized in crowd counting. Humans glance at a crowd image and instantly know the approximate number…

cs.LG2021★ 5 cited

Conditional Contrastive Learning for Improving Fairness in Self-Supervised Learning

Martin Q. Ma, Yao-Hung Hubert Tsai, Paul Pu Liang +4

Contrastive self-supervised learning (SSL) learns an embedding space that maps similar data pairs closer and dissimilar data pairs farther apart. Despite its success, one issue has…