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Yibo Zeng

2 accepted papers

2022

Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization

NeurIPS 2022accept

Established approaches to obtain generalization bounds in data-driven optimization and machine learning mostly build on solutions from empirical risk minimization (ERM), which depend crucially on the functional complexity of the hypothesis class. In this paper, we present an alternate route to obtai…

Cited by 15SourcePDFScholar
2020

AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Discounted Markov Decision Processes with Near-Optimal Sample Complexity

AISTATS 2020poster

In this paper, we propose AsyncQVI, an asynchronous-parallel Q-value iteration for discounted Markov decision processes whose transition and reward can only be sampled through a generative model. AsyncQVI is also the first asynchronous-parallel algorithm for discounted Markov decision processes that…