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stat.ML2022★ 1 cited
Generalization Bounds for Stochastic Gradient Descent via Localized -Covers
Sejun Park, Umut Şimşekli, Murat A. Erdogdu
In this paper, we propose a new covering technique localized for the trajectories of SGD. This localization provides an algorithm-specific complexity measured by the covering numbe…
stat.ML2020
Learning Bounds for Risk-sensitive Learning
Jaeho Lee, Sejun Park, Jinwoo Shin
In risk-sensitive learning, one aims to find a hypothesis that minimizes a risk-averse (or risk-seeking) measure of loss, instead of the standard expected loss. In this paper, we p…