Zimmert, Julian

32 publications

NeurIPS 2025 Contextual Dynamic Pricing with Heterogeneous Buyers Thodoris Lykouris, Sloan Nietert, Princewill Okoroafor, Chara Podimata, Julian Zimmert

NeurIPS 2025 Non-Stationary Bandit Convex Optimization: A Comprehensive Study Xiaoqi Liu, Dorian Baudry, Julian Zimmert, Patrick Rebeschini, Arya Akhavan

NeurIPS 2024 A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback with Robustness to Excessive Delays Saeed Masoudian, Julian Zimmert, Yevgeny Seldin

ICMLW 2024 A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback with Robustness to Excessive Delays Saeed Masoudian, Julian Zimmert, Yevgeny Seldin

NeurIPS 2024 Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback Haolin Liu, Zakaria Mhammedi, Chen-Yu Wei, Julian Zimmert

NeurIPS 2024 PRODuctive Bandits: Importance Weighting No More Julian Zimmert, Teodor V. Marinov

ICLR 2024 Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback Haolin Liu, Chen-Yu Wei, Julian Zimmert

COLT 2023 A Blackbox Approach to Best of Both Worlds in Bandits and Beyond Chris Dann, Chen-Yu Wei, Julian Zimmert

ALT 2023 A Unified Algorithm for Stochastic Path Problems Christoph Dann, Chen-Yu Wei, Julian Zimmert

ICML 2023 Best of Both Worlds Policy Optimization Christoph Dann, Chen-Yu Wei, Julian Zimmert

NeurIPS 2023 Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits Haolin Liu, Chen-Yu Wei, Julian Zimmert

NeurIPS 2023 Optimal Cross-Learning for Contextual Bandits with Unknown Context Distributions Jon Schneider, Julian Zimmert

ICML 2023 Refined Regret for Adversarial MDPs with Linear Function Approximation Yan Dai, Haipeng Luo, Chen-Yu Wei, Julian Zimmert

NeurIPS 2022 A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback Saeed Masoudian, Julian Zimmert, Yevgeny Seldin

ALT 2022 A Model Selection Approach for Corruption Robust Reinforcement Learning Chen-Yu Wei, Christoph Dann, Julian Zimmert

ALT 2022 Efficient Methods for Online Multiclass Logistic Regression Naman Agarwal, Satyen Kale, Julian Zimmert

COLT 2022 Open Problem: Finite-Time Instance Dependent Optimality for Stochastic Online Learning with Feedback Graphs Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert

COLT 2022 Pushing the Efficiency-Regret Pareto Frontier for Online Learning of Portfolios and Quantum States Julian Zimmert, Naman Agarwal, Satyen Kale

COLT 2022 Return of the Bias: Almost Minimax Optimal High Probability Bounds for Adversarial Linear Bandits Julian Zimmert, Tor Lattimore

NeurIPS 2022 Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert

NeurIPS 2021 A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert

NeurIPS 2021 Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning Christoph Dann, Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert

NeurIPS 2021 The Pareto Frontier of Model Selection for General Contextual Bandits Teodor Vanislavov Marinov, Julian Zimmert

JMLR 2021 Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits Julian Zimmert, Yevgeny Seldin

NeurIPS 2020 Adapting to Misspecification in Contextual Bandits Dylan J Foster, Claudio Gentile, Mehryar Mohri, Julian Zimmert

AISTATS 2020 An Optimal Algorithm for Adversarial Bandits with Arbitrary Delays Julian Zimmert, Yevgeny Seldin

NeurIPS 2020 Model Selection in Contextual Stochastic Bandit Problems Aldo Pacchiano, My Phan, Yasin Abbasi Yadkori, Anup Rao, Julian Zimmert, Tor Lattimore, Csaba Szepesvari

ICML 2020 Online Learning for Active Cache Synchronization Andrey Kolobov, Sebastien Bubeck, Julian Zimmert

AISTATS 2019 An Optimal Algorithm for Stochastic and Adversarial Bandits Julian Zimmert, Yevgeny Seldin

ICML 2019 Beating Stochastic and Adversarial Semi-Bandits Optimally and Simultaneously Julian Zimmert, Haipeng Luo, Chen-Yu Wei

NeurIPS 2019 Connections Between Mirror Descent, Thompson Sampling and the Information Ratio Julian Zimmert, Tor Lattimore

NeurIPS 2018 Factored Bandits Julian Zimmert, Yevgeny Seldin