Distributed Optimization of Multi-Class SVMs. - Maximilian Alber; Julian Zimmert; Ürün Dogan; Marius Kloft (CoRR, 2016)

Factored Bandits. - Julian Zimmert; Yevgeny Seldin (NeurIPS, 2018)

An Optimal Algorithm for Stochastic and Adversarial Bandits. - Julian Zimmert; Yevgeny Seldin (AISTATS, 2019)

Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously. - Julian Zimmert; Haipeng Luo; Chen-Yu Wei (ICML, 2019)

Connections Between Mirror Descent, Thompson Sampling and the Information Ratio. - Julian Zimmert; Tor Lattimore (NeurIPS, 2019)

An Optimal Algorithm for Adversarial Bandits with Arbitrary Delays. - Julian Zimmert; Yevgeny Seldin (AISTATS, 2020)

Online Learning for Active Cache Synchronization. - Andrey Kolobov; Sébastien Bubeck; Julian Zimmert (ICML, 2020)

Adapting to Misspecification in Contextual Bandits. - Dylan J. Foster; Claudio Gentile; Mehryar Mohri; Julian Zimmert (NeurIPS, 2020)

Model Selection in Contextual Stochastic Bandit Problems. - Aldo Pacchiano; My Phan; Yasin Abbasi-Yadkori; Anup Rao 002; Julian Zimmert; Tor Lattimore; Csaba Szepesvári (NeurIPS, 2020)

Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning. - Christoph Dann; 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 001; Julian Zimmert (NeurIPS, 2021)

The Pareto Frontier of model selection for general Contextual Bandits. - Teodor Vanislavov Marinov; Julian Zimmert (NeurIPS, 2021)

Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits. - Julian Zimmert; Yevgeny Seldin (J. Mach. Learn. Res., 2021)

Efficient Methods for Online Multiclass Logistic Regression. - Naman Agarwal; Satyen Kale; Julian Zimmert (ALT, 2022)

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

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

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

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

A Blackbox Approach to Best of Both Worlds in Bandits and Beyond. - Christoph Dann; Chen-Yu Wei; Julian Zimmert (COLT, 2023)

Refined Regret for Adversarial MDPs with Linear Function Approximation. - Yan Dai 002; Haipeng Luo; Chen-Yu Wei; Julian Zimmert (ICML, 2023)

Best of Both Worlds Policy Optimization. - Christoph Dann; Chen-Yu Wei; Julian Zimmert (ICML, 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 (NeurIPS, 2023)

An Improved Best-of-both-worlds Algorithm for Bandits with Delayed Feedback. - Saeed Masoudian; Julian Zimmert; Yevgeny Seldin (CoRR, 2023)

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

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

PRODuctive bandits: Importance Weighting No More. - Julian Zimmert; Teodor Vanislavov Marinov (NeurIPS, 2024)

Incentive-compatible Bandits: Importance Weighting No More. - Julian Zimmert; Teodor V. Marinov (CoRR, 2024)

Decision Making in Hybrid Environments: A Model Aggregation Approach. - Haolin Liu; Chen-Yu Wei; Julian Zimmert (COLT, 2025)

A Scalable Crawling Algorithm Utilizing Noisy Change-Indicating Signals. - Julian Zimmert; Róbert Busa-Fekete; András György 001; Linhai Qiu; Hyomin Choi; Tzu-Wei Sung; Hao Shen; Sharmila Subramaniam; Li Xiao (WWW, 2025)

Non-stationary Bandit Convex Optimization: A Comprehensive Study. - Xiaoqi Liu; Dorian Baudry; Julian Zimmert; Patrick Rebeschini; Arya Akhavan (CoRR, 2025)

Beyond the Rosetta Stone: Unification Forces in Generalization Dynamics. - Carter Blum; Katja Filippova; Ann Yuan; Asma Ghandeharioun; Julian Zimmert; Fred Zhang; Jessica Hoffmann; Tal Linzen; Martin Wattenberg; Lucas Dixon; Mor Geva (CoRR, 2025)