Julian Zimmert

According to our database, Julian Zimmert authored at least 27 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback.

Haolin Liu, Chen-Yu Wei, Julian Zimmert

CoRR, 2023

An Improved Best-of-both-worlds Algorithm for Bandits with Delayed Feedback.

Saeed Masoudian, Julian Zimmert, Yevgeny Seldin

CoRR, 2023

Optimal cross-learning for contextual bandits with unknown context distributions.

Jon Schneider, Julian Zimmert

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits.

Haolin Liu, Chen-Yu Wei, Julian Zimmert

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Best of Both Worlds Policy Optimization.

Christoph Dann, Chen-Yu Wei, Julian Zimmert

Proceedings of the International Conference on Machine Learning, 2023

Refined Regret for Adversarial MDPs with Linear Function Approximation.

Yan Dai, Haipeng Luo, Chen-Yu Wei, Julian Zimmert

Proceedings of the International Conference on Machine Learning, 2023

A Blackbox Approach to Best of Both Worlds in Bandits and Beyond.

Christoph Dann, Chen-Yu Wei, Julian Zimmert

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

A Unified Algorithm for Stochastic Path Problems.

Christoph Dann, Chen-Yu Wei, Julian Zimmert

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

2022

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

Saeed Masoudian, Julian Zimmert, Yevgeny Seldin

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Return of the bias: Almost minimax optimal high probability bounds for adversarial linear bandits.

Julian Zimmert, Tor Lattimore

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Pushing the Efficiency-Regret Pareto Frontier for Online Learning of Portfolios and Quantum States.

Julian Zimmert, Naman Agarwal, Satyen Kale

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

A Model Selection Approach for Corruption Robust Reinforcement Learning.

Chen-Yu Wei, Christoph Dann, Julian Zimmert

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Efficient Methods for Online Multiclass Logistic Regression.

Naman Agarwal, Satyen Kale, Julian Zimmert

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

2021

Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits.

Julian Zimmert, Yevgeny Seldin

J. Mach. Learn. Res., 2021

The Pareto Frontier of model selection for general Contextual Bandits.

Teodor Vanislavov Marinov, Julian Zimmert

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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

Christoph Dann, Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Model Selection in Contextual Stochastic Bandit Problems.

Aldo Pacchiano, My Phan, Yasin Abbasi-Yadkori, Anup Rao, Julian Zimmert, Tor Lattimore, Csaba Szepesvári

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Adapting to Misspecification in Contextual Bandits.

Dylan J. Foster, Claudio Gentile, Mehryar Mohri, Julian Zimmert

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Online Learning for Active Cache Synchronization.

Andrey Kolobov, Sébastien Bubeck, Julian Zimmert

Proceedings of the 37th International Conference on Machine Learning, 2020

An Optimal Algorithm for Adversarial Bandits with Arbitrary Delays.

Julian Zimmert, Yevgeny Seldin

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Connections Between Mirror Descent, Thompson Sampling and the Information Ratio.

Julian Zimmert, Tor Lattimore

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously.

Julian Zimmert, Haipeng Luo, Chen-Yu Wei

Proceedings of the 36th International Conference on Machine Learning, 2019

An Optimal Algorithm for Stochastic and Adversarial Bandits.

Julian Zimmert, Yevgeny Seldin

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Factored Bandits.

Julian Zimmert, Yevgeny Seldin

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016

Distributed Optimization of Multi-Class SVMs.

Maximilian Alber, Julian Zimmert, Ürün Dogan, Marius Kloft

CoRR, 2016