Ronald Ortner - RankMe

57 papers A* 8A 4B 5Journal 31Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Quantification of transfer in reinforcement learning via regret bounds for learning agents. Auton. Agents Multi Agent Syst. Adrienne Tuynman, Ronald Ortner
2025	J	`jnl`	On cubic vertex-transitive graphs of given girth. Art Discret. Appl. Math. Ted Dobson, Ademir Hujdurovic, Wilfried Imrich, Ronald Ortner
2023	A*	`conf`	Autonomous Exploration for Navigating in MDPs Using Blackbox RL Algorithms. IJCAI Pratik Gajane, Peter Auer, Ronald Ortner
2023	J	`jnl`	Regret Bounds for Satisficing in Multi-Armed Bandit Problems. Trans. Mach. Learn. Res. Thomas Michel, Hossein Hajiabolhassan, Ronald Ortner
2022	—	`book`	Decision Making Under Uncertainty and Reinforcement Learning - Theory and Algorithms Christos Dimitrakakis, Ronald Ortner
2022	J	`jnl`	Predicting Packaging Sizes Using Machine Learning. Oper. Res. Forum Michael Heininger, Ronald Ortner
2022	J	`jnl`	Transfer in Reinforcement Learning via Regret Bounds for Learning Agents. CoRR Adrienne Tuynman, Ronald Ortner
2021	J	`jnl`	A new heuristic and an exact approach for a production planning problem. Central Eur. J. Oper. Res. Peter Auer, György Dósa, Tibor Dulai, Armin Fügenschuh, Peggy Näser, Ronald Ortner, Agnes Werner-Stark
2020	J	`jnl`	Regret Bounds for Reinforcement Learning via Markov Chain Concentration. J. Artif. Intell. Res. Ronald Ortner
2019	A*	`conf`	Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information. COLT Peter Auer, Yifang Chen, Pratik Gajane, Chung-wei Lee, Haipeng Luo, Ronald Ortner, Chen-Yu Wei
2019	A*	`conf`	Adaptively Tracking the Best Bandit Arm with an Unknown Number of Distribution Changes. COLT Peter Auer, Pratik Gajane, Ronald Ortner
2019	J	`jnl`	Autonomous exploration for navigating in non-stationary CMPs. CoRR Pratik Gajane, Ronald Ortner, Peter Auer, Csaba Szepesvári
2019	A*	`conf`	Regret Bounds for Learning State Representations in Reinforcement Learning. NeurIPS Ronald Ortner, Matteo Pirotta, Alessandro Lazaric, Ronan Fruit, Odalric-Ambrym Maillard
2019	A	`conf`	Variational Regret Bounds for Reinforcement Learning. UAI Ronald Ortner, Pratik Gajane, Peter Auer
2019	J	`jnl`	Variational Regret Bounds for Reinforcement Learning. CoRR Pratik Gajane, Ronald Ortner, Peter Auer
2018	J	`jnl`	A Sliding-Window Algorithm for Markov Decision Processes with Arbitrarily Changing Rewards and Transitions. CoRR Pratik Gajane, Ronald Ortner, Peter Auer
2018	A*	`conf`	Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning. ICML Ronan Fruit, Matteo Pirotta, Alessandro Lazaric, Ronald Ortner
2018	J	`jnl`	Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning. CoRR Ronan Fruit, Matteo Pirotta, Alessandro Lazaric, Ronald Ortner
2018	J	`jnl`	Guest Editors' Foreword. Theor. Comput. Sci. Ronald Ortner, Hans Ulrich Simon
2018	J	`jnl`	Regret Bounds for Reinforcement Learning via Markov Chain Concentration. CoRR Ronald Ortner
2016	B	`ed.`	Algorithmic Learning Theory - 27th International Conference, ALT 2016, Bari, Italy, October 19-21, 2016, Proceedings ALT Ronald Ortner, Hans Ulrich Simon, Sandra Zilles
2016	A	`conf`	Improved Learning Complexity in Combinatorial Pure Exploration Bandits. AISTATS Victor Gabillon, Alessandro Lazaric, Mohammad Ghavamzadeh, Ronald Ortner, Peter L. Bartlett
2016	J	`jnl`	Optimal Behavior is Easier to Learn than the Truth. Minds Mach. Ronald Ortner
2016	A	`conf`	Pareto Front Identification from Stochastic Bandit Feedback. AISTATS Peter Auer, Chao-Kai Chiang, Ronald Ortner, Madalina M. Drugan
2015	J	`jnl`	Forcing subarrangements in complete arrangements of pseudocircles. J. Comput. Geom. Ronald Ortner
2015	A*	`conf`	Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning. ICML K. Lakshmanan, Ronald Ortner, Daniil Ryabko
2014	J	`jnl`	Regret bounds for restless Markov bandits. Theor. Comput. Sci. Ronald Ortner, Daniil Ryabko, Peter Auer, Rémi Munos
2014	B	`conf`	Selecting Near-Optimal Approximate State Representations in Reinforcement Learning. ALT Ronald Ortner, Odalric-Ambrym Maillard, Daniil Ryabko
2014	J	`jnl`	Selecting Near-Optimal Approximate State Representations in Reinforcement Learning. CoRR Ronald Ortner, Odalric-Ambrym Maillard, Daniil Ryabko
2013	J	`jnl`	Adaptive aggregation for reinforcement learning in average reward Markov decision processes. Ann. Oper. Res. Ronald Ortner
2013	A	`conf`	Competing with an Infinite Set of Models in Reinforcement Learning. AISTATS Phuong Nguyen, Odalric-Ambrym Maillard, Daniil Ryabko, Ronald Ortner
2013	J	`jnl`	Online Regret Bounds for Undiscounted Continuous Reinforcement Learning CoRR Ronald Ortner, Daniil Ryabko
2013	J	`jnl`	Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning CoRR Odalric-Ambrym Maillard, Phuong Nguyen, Ronald Ortner, Daniil Ryabko
2013	—	`conf`	Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning. ICML (1) Odalric-Ambrym Maillard, Phuong Nguyen, Ronald Ortner, Daniil Ryabko
2012	—	`conf`	Online Regret Bounds for Undiscounted Continuous Reinforcement Learning. NIPS Ronald Ortner, Daniil Ryabko
2012	J	`jnl`	Regret Bounds for Restless Markov Bandits CoRR Ronald Ortner, Daniil Ryabko, Peter Auer, Rémi Munos
2012	B	`conf`	Regret Bounds for Restless Markov Bandits. ALT Ronald Ortner, Daniil Ryabko, Peter Auer, Rémi Munos
2011	—	`ch.`	Mechanizing Induction. Inductive Logic Ronald Ortner, Hannes Leitgeb
2011	—	`conf`	PAC-Bayesian Analysis of Contextual Bandits. NIPS Yevgeny Seldin, Peter Auer, François Laviolette, John Shawe-Taylor, Ronald Ortner
2010	—	`conf`	Exploiting Similarity Information in Reinforcement Learning - Similarity Models for Multi-Armed Bandits and MDPs. ICAART (1) Ronald Ortner
2010	J	`jnl`	Near-optimal Regret Bounds for Reinforcement Learning. J. Mach. Learn. Res. Thomas Jaksch, Ronald Ortner, Peter Auer
2010	J	`jnl`	Online regret bounds for Markov decision processes with deterministic transitions. Theor. Comput. Sci. Ronald Ortner
2010	J	`jnl`	UCB revisited: Improved regret bounds for the stochastic multi-armed bandit problem. Period. Math. Hung. Peter Auer, Ronald Ortner
2008	J	`jnl`	Embeddability of arrangements of pseudocircles into the sphere. Eur. J. Comb. Ronald Ortner
2008	—	`conf`	Near-optimal Regret Bounds for Reinforcement Learning. NIPS Peter Auer, Thomas Jaksch, Ronald Ortner
2008	B	`conf`	Online Regret Bounds for Markov Decision Processes with Deterministic Transitions. ALT Ronald Ortner
2008	J	`jnl`	Optimism in the Face of Uncertainty Should be Refutable. Minds Mach. Ronald Ortner
2007	J	`jnl`	A new PAC bound for intersection-closed concept classes. Mach. Learn. Peter Auer, Ronald Ortner
2007	A*	`conf`	Improved Rates for the Stochastic Continuum-Armed Bandit Problem. COLT Peter Auer, Ronald Ortner, Csaba Szepesvári
2007	J	`jnl`	Linear dependence of stationary distributions in ergodic Markov decision processes. Oper. Res. Lett. Ronald Ortner
2007	B	`conf`	Pseudometrics for State Aggregation in Average Reward Markov Decision Processes. ALT Ronald Ortner
2006	—	`conf`	Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning. NIPS Peter Auer, Ronald Ortner
2005	J	`jnl`	Combinations and Mixtures of Optimal Policies in Unichain Markov Decision Processes are Optimal CoRR Ronald Ortner
2005	J	`jnl`	Embeddability of Arrangements of Pseudocircles into the Sphere CoRR Ronald Ortner
2004	—	`conf`	A Boosting Approach to Multiple Instance Learning. ECML Peter Auer, Ronald Ortner
2004	A*	`conf`	A New PAC Bound for Intersection-Closed Concept Classes. COLT Peter Auer, Ronald Ortner
2004	J	`jnl`	On the Combinatorial Structure of Arrangements of Oriented Pseudocircles. Electron. J. Comb. Johann Linhart, Ronald Ortner