3 papers
cs.LG2026
Attribute-Efficient PAC Learning of Sparse Halfspaces with Constant Malicious Noise Rate
Shiwei Zeng, Jie Shen
Attribute-efficient PAC learning of sparse halfspaces has been a fundamental problem in machine learning theory. In recent years, machine learning algorithms are faced with prevale…
cs.LG2025
Towards Efficient Contrastive PAC Learning
Jie Shen
We study contrastive learning under the PAC learning framework. While a series of recent works have shown statistical results for learning under contrastive loss, based either on t…
cs.LG2025
Efficient PAC Learning of Halfspaces with Constant Malicious Noise Rate
Jie Shen
Understanding noise tolerance of machine learning algorithms is a central quest in learning theory. In this work, we study the problem of computationally efficient PAC learning of…