Ronald Ortner

Publication Activity (10 Years)

Years Active: 2004-2023
Publications (10 Years): 22

Top Topics

Markov Decision Process

Reinforcement Learning

Top Venues

Theor. Comput. Sci.

Publications

Thomas Michel, Hossein Hajiabolhassan, Ronald Ortner
Regret Bounds for Satisficing in Multi-Armed Bandit Problems. Trans. Mach. Learn. Res. 2023 (2023)
Pratik Gajane, Peter Auer, Ronald Ortner
Autonomous Exploration for Navigating in MDPs Using Blackbox RL Algorithms. IJCAI (2023)
Michael Heininger, Ronald Ortner
Predicting Packaging Sizes Using Machine Learning. Oper. Res. Forum 3 (3) (2022)
Adrienne Tuynman, Ronald Ortner
Transfer in Reinforcement Learning via Regret Bounds for Learning Agents. CoRR (2022)
Peter Auer, György Dósa, Tibor Dulai, Armin Fügenschuh, Peggy Näser, Ronald Ortner, Agnes Werner-Stark
A new heuristic and an exact approach for a production planning problem. Central Eur. J. Oper. Res. 29 (3) (2021)
Ronald Ortner
Regret Bounds for Reinforcement Learning via Markov Chain Concentration. J. Artif. Intell. Res. 67 (2020)
Ronald Ortner, Matteo Pirotta, Alessandro Lazaric, Ronan Fruit, Odalric-Ambrym Maillard
Regret Bounds for Learning State Representations in Reinforcement Learning. NeurIPS (2019)
Peter Auer, Yifang Chen, Pratik Gajane, Chung-Wei Lee, Haipeng Luo, Ronald Ortner, Chen-Yu Wei
Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information. COLT (2019)
Ronald Ortner, Pratik Gajane, Peter Auer
Variational Regret Bounds for Reinforcement Learning. UAI (2019)
Pratik Gajane, Ronald Ortner, Peter Auer
Variational Regret Bounds for Reinforcement Learning. CoRR (2019)
Pratik Gajane, Ronald Ortner, Peter Auer, Csaba Szepesvári
Autonomous exploration for navigating in non-stationary CMPs. CoRR (2019)
Peter Auer, Pratik Gajane, Ronald Ortner
Adaptively Tracking the Best Bandit Arm with an Unknown Number of Distribution Changes. COLT (2019)
Pratik Gajane, Ronald Ortner, Peter Auer
A Sliding-Window Algorithm for Markov Decision Processes with Arbitrarily Changing Rewards and Transitions. CoRR (2018)
Ronan Fruit, Matteo Pirotta, Alessandro Lazaric, Ronald Ortner
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning. CoRR (2018)
Ronald Ortner
Regret Bounds for Reinforcement Learning via Markov Chain Concentration. CoRR (2018)
Ronald Ortner, Hans Ulrich Simon
Guest Editors' Foreword. Theor. Comput. Sci. 742 (2018)
Ronan Fruit, Matteo Pirotta, Alessandro Lazaric, Ronald Ortner
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning. ICML (2018)
Victor Gabillon, Alessandro Lazaric, Mohammad Ghavamzadeh, Ronald Ortner, Peter L. Bartlett
Improved Learning Complexity in Combinatorial Pure Exploration Bandits. AISTATS (2016)
Ronald Ortner
Optimal Behavior is Easier to Learn than the Truth. Minds Mach. 26 (3) (2016)
Peter Auer, Chao-Kai Chiang, Ronald Ortner, Madalina M. Drugan
Pareto Front Identification from Stochastic Bandit Feedback. AISTATS (2016)
K. Lakshmanan, Ronald Ortner, Daniil Ryabko
Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning. ICML (2015)
Ronald Ortner
Forcing subarrangements in complete arrangements of pseudocircles. J. Comput. Geom. 6 (1) (2015)
Ronald Ortner, Odalric-Ambrym Maillard, Daniil Ryabko
Selecting Near-Optimal Approximate State Representations in Reinforcement Learning. ALT (2014)
Ronald Ortner, Odalric-Ambrym Maillard, Daniil Ryabko
Selecting Near-Optimal Approximate State Representations in Reinforcement Learning. CoRR (2014)
Ronald Ortner, Daniil Ryabko, Peter Auer, Rémi Munos
Regret bounds for restless Markov bandits. Theor. Comput. Sci. 558 (2014)
Odalric-Ambrym Maillard, Phuong Nguyen, Ronald Ortner, Daniil Ryabko
Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning CoRR (2013)
Ronald Ortner
Adaptive aggregation for reinforcement learning in average reward Markov decision processes. Ann. Oper. Res. 208 (1) (2013)
Phuong Nguyen, Odalric-Ambrym Maillard, Daniil Ryabko, Ronald Ortner
Competing with an Infinite Set of Models in Reinforcement Learning. AISTATS (2013)
Odalric-Ambrym Maillard, Phuong Nguyen, Ronald Ortner, Daniil Ryabko
Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning. ICML (1) (2013)
Ronald Ortner, Daniil Ryabko
Online Regret Bounds for Undiscounted Continuous Reinforcement Learning CoRR (2013)
Ronald Ortner, Daniil Ryabko, Peter Auer, Rémi Munos
Regret Bounds for Restless Markov Bandits. ALT (2012)
Ronald Ortner, Daniil Ryabko
Online Regret Bounds for Undiscounted Continuous Reinforcement Learning. NIPS (2012)
Ronald Ortner, Daniil Ryabko, Peter Auer, Rémi Munos
Regret Bounds for Restless Markov Bandits CoRR (2012)
Yevgeny Seldin, Peter Auer, François Laviolette, John Shawe-Taylor, Ronald Ortner
PAC-Bayesian Analysis of Contextual Bandits. NIPS (2011)
Ronald Ortner
Online regret bounds for Markov decision processes with deterministic transitions. Theor. Comput. Sci. 411 (29-30) (2010)
Thomas Jaksch, Ronald Ortner, Peter Auer
Near-optimal Regret Bounds for Reinforcement Learning. J. Mach. Learn. Res. 11 (2010)
Ronald Ortner
Exploiting Similarity Information in Reinforcement Learning - Similarity Models for Multi-Armed Bandits and MDPs. ICAART (1) (2010)
Peter Auer, Ronald Ortner
UCB revisited: Improved regret bounds for the stochastic multi-armed bandit problem. Period. Math. Hung. 61 (1-2) (2010)
Ronald Ortner
Optimism in the Face of Uncertainty Should be Refutable. Minds Mach. 18 (4) (2008)
Ronald Ortner
Online Regret Bounds for Markov Decision Processes with Deterministic Transitions. ALT (2008)
Ronald Ortner
Embeddability of arrangements of pseudocircles into the sphere. Eur. J. Comb. 29 (2) (2008)
Peter Auer, Thomas Jaksch, Ronald Ortner
Near-optimal Regret Bounds for Reinforcement Learning. NIPS (2008)
Ronald Ortner
Linear dependence of stationary distributions in ergodic Markov decision processes. Oper. Res. Lett. 35 (5) (2007)
Peter Auer, Ronald Ortner, Csaba Szepesvári
Improved Rates for the Stochastic Continuum-Armed Bandit Problem. COLT (2007)
Ronald Ortner
Pseudometrics for State Aggregation in Average Reward Markov Decision Processes. ALT (2007)
Peter Auer, Ronald Ortner
A new PAC bound for intersection-closed concept classes. Mach. Learn. 66 (2-3) (2007)
Peter Auer, Ronald Ortner
Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning. NIPS (2006)
Ronald Ortner
Combinations and Mixtures of Optimal Policies in Unichain Markov Decision Processes are Optimal CoRR (2005)
Ronald Ortner
Embeddability of Arrangements of Pseudocircles into the Sphere CoRR (2005)
Peter Auer, Ronald Ortner
A New PAC Bound for Intersection-Closed Concept Classes. COLT (2004)
Johann Linhart, Ronald Ortner
On the Combinatorial Structure of Arrangements of Oriented Pseudocircles. Electron. J. Comb. 11 (1) (2004)
Peter Auer, Ronald Ortner
A Boosting Approach to Multiple Instance Learning. ECML (2004)