62 citations · 244 across the 20 of their papers we have counts for
5 papers · 1 filter
A Second-Order Approach to Learning with Instance-Dependent Label Noise
Zhaowei Zhu, Tongliang Liu, Yang Liu
The presence of label noise often misleads the training of deep neural networks. Departing from the recent literature which largely assumes the label noise rate is only determined…
Linear Classifiers that Encourage Constructive Adaptation
Yatong Chen, Jialu Wang, Yang Liu
Machine learning systems are often used in settings where individuals adapt their features to obtain a desired outcome. In such settings, strategic behavior leads to a sharp loss i…
Federated Bandit: A Gossiping Approach
Zhaowei Zhu, Jingxuan Zhu, Ji Liu +1
In this paper, we study \emph{Federated Bandit}, a decentralized Multi-Armed Bandit problem with a set of agents, who can only communicate their local data with neighbors descr…
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach
Hao Cheng, Zhaowei Zhu, Xingyu Li +3
Human-annotated labels are often prone to noise, and the presence of such noise will degrade the performance of the resulting deep neural network (DNN) models. Much of the literatu…
Policy Learning Using Weak Supervision
Jingkang Wang, Hongyi Guo, Zhaowei Zhu +1
Most existing policy learning solutions require the learning agents to receive high-quality supervision signals such as well-designed rewards in reinforcement learning (RL) or high…