Work

Bridging the Gap: Rademacher Complexity in Robust and Standard Generalization

Year: 2024

Type: article

Abstract: , specifically designed and proven to reconcile these two properties. Consequently, our method effectively bridges the gap between Rademacher complexity in robust and standard generalization.

Source: PubMed

DOI: 10.48550/arxiv.2406.05372

Authors: Xiao, Jiancong, Sun, Ruoyu, Long, Qi, Su, Weijie J.

Institutions: University of Pennsylvania, Chinese University of Hong Kong, Shenzhen

Language: English

Topic: Stochastic Gradient Optimization Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, National Institutes of Health, National Institute on Aging, National Cancer Institute

Awards: Advancing Analysis of Multi-omics Data in Alzheimer's Disease Research, Geometrization Approaches toward Understanding Deep Learning, Robust privacy preserving distributed analysis platform for cancer research: addressing biased, incomplete data

OpenAlex ID: W4399554697

FWCI:

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