Julian Zimmert

papers

355

total citations

papers (10)

Model Selection in Contextual Stochastic Bandit Problems

NEURIPS 2020arXiv

102

citations

Adapting to Misspecification in Contextual Bandits

NEURIPS 2020arXiv

citations

A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning

NEURIPS 2021arXiv

citations

Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning

NEURIPS 2021arXiv

citations

Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality

NEURIPS 2022arXiv

citations

Optimal cross-learning for contextual bandits with unknown context distributions

NEURIPS 2023arXiv

citations

Contextual Dynamic Pricing with Heterogeneous Buyers

NEURIPS 2025arXiv

citations

Julian Zimmert

papers (10)

Model Selection in Contextual Stochastic Bandit Problems

Adapting to Misspecification in Contextual Bandits

A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning

Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning

The Pareto Frontier of model selection for general Contextual Bandits

A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback

Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits

Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality

Optimal cross-learning for contextual bandits with unknown context distributions

Contextual Dynamic Pricing with Heterogeneous Buyers

papers (10)

Model Selection in Contextual Stochastic Bandit Problems

Adapting to Misspecification in Contextual Bandits

A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning

Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning

The Pareto Frontier of model selection for general Contextual Bandits

A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback

Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits

Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality

Optimal cross-learning for contextual bandits with unknown context distributions

Contextual Dynamic Pricing with Heterogeneous Buyers