Ortner, Ronald

27 publications

IJCAI 2023 Autonomous Exploration for Navigating in MDPs Using Blackbox RL Algorithms Pratik Gajane, Peter Auer, Ronald Ortner

TMLR 2023 Regret Bounds for Satisficing in Multi-Armed Bandit Problems Thomas Michel, Hossein Hajiabolhassan, Ronald Ortner

JAIR 2020 Regret Bounds for Reinforcement Learning via Markov Chain Concentration Ronald Ortner

COLT 2019 Achieving Optimal Dynamic Regret for Non-Stationary Bandits Without Prior Information Peter Auer, Yifang Chen, Pratik Gajane, Chung-Wei Lee, Haipeng Luo, Ronald Ortner, Chen-Yu Wei

COLT 2019 Adaptively Tracking the Best Bandit Arm with an Unknown Number of Distribution Changes Peter Auer, Pratik Gajane, Ronald Ortner

NeurIPS 2019 Regret Bounds for Learning State Representations in Reinforcement Learning Ronald Ortner, Matteo Pirotta, Alessandro Lazaric, Ronan Fruit, Odalric-Ambrym Maillard

UAI 2019 Variational Regret Bounds for Reinforcement Learning Ronald Ortner, Pratik Gajane, Peter Auer

ICML 2018 Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning Ronan Fruit, Matteo Pirotta, Alessandro Lazaric, Ronald Ortner

ALT 2016 Algorithmic Learning Theory - 27th International Conference, ALT 2016, Bari, Italy, October 19-21, 2016, Proceedings Ronald Ortner, Hans Ulrich Simon, Sandra Zilles

AISTATS 2016 Improved Learning Complexity in Combinatorial Pure Exploration Bandits Victor Gabillon, Alessandro Lazaric, Mohammad Ghavamzadeh, Ronald Ortner, Peter L. Bartlett

AISTATS 2016 Pareto Front Identification from Stochastic Bandit Feedback Peter Auer, Chao-Kai Chiang, Ronald Ortner, Madalina M. Drugan

ICML 2015 Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning K. Lakshmanan, Ronald Ortner, Daniil Ryabko

ALT 2014 Selecting Near-Optimal Approximate State Representations in Reinforcement Learning Ronald Ortner, Odalric-Ambrym Maillard, Daniil Ryabko

AISTATS 2013 Competing with an Infinite Set of Models in Reinforcement Learning Phuong Nguyen, Odalric-Ambrym Maillard, Daniil Ryabko, Ronald Ortner

ICML 2013 Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning Odalric-Ambrym Maillard, Phuong Nguyen, Ronald Ortner, Daniil Ryabko

NeurIPS 2012 Online Regret Bounds for Undiscounted Continuous Reinforcement Learning Ronald Ortner, Daniil Ryabko

ALT 2012 Regret Bounds for Restless Markov Bandits Ronald Ortner, Daniil Ryabko, Peter Auer, Rémi Munos

NeurIPS 2011 PAC-Bayesian Analysis of Contextual Bandits Yevgeny Seldin, Peter Auer, John S. Shawe-taylor, Ronald Ortner, François Laviolette

JMLR 2010 Near-Optimal Regret Bounds for Reinforcement Learning Thomas Jaksch, Ronald Ortner, Peter Auer

NeurIPS 2008 Near-Optimal Regret Bounds for Reinforcement Learning Peter Auer, Thomas Jaksch, Ronald Ortner

ALT 2008 Online Regret Bounds for Markov Decision Processes with Deterministic Transitions Ronald Ortner

MLJ 2007 A New PAC Bound for Intersection-Closed Concept Classes Peter Auer, Ronald Ortner

COLT 2007 Improved Rates for the Stochastic Continuum-Armed Bandit Problem Peter Auer, Ronald Ortner, Csaba Szepesvári

ALT 2007 Pseudometrics for State Aggregation in Average Reward Markov Decision Processes Ronald Ortner

NeurIPS 2006 Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning Peter Auer, Ronald Ortner

ECML-PKDD 2004 A Boosting Approach to Multiple Instance Learning Peter Auer, Ronald Ortner

COLT 2004 A New PAC Bound for Intersection-Closed Concept Classes Peter Auer, Ronald Ortner