← Authors

Ronald Ortner

16 papers · 2006–2023 · 7 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (17) 🐝 Cross-Pollinator (15) πŸ—ΊοΈ Taxonomy Completionist (21) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (7) 🌱 Topic Pioneer πŸ† Keyword Champion πŸ”¬ Deep Specialist (12) πŸ—ƒοΈ Keyword Collector (51) πŸ“ˆ Trend Setter πŸ’Ž Century Club (16) πŸš€ Conference Pioneer

Conferences

NIPS (5) AISTATS (3) ICML (3) COLT (2) IJCAI (1) JMLR (1) UAI (1)

Top co-authors

Peter Auer (9) Daniil Ryabko (4) Pratik Gajane (4) Odalric-ambrym Maillard (3) Alessandro Lazaric (3) Phuong Nguyen (2) Matteo Pirotta (2) Ronan Fruit (2) Thomas Jaksch (2) Chung-Wei Lee (1)

Research topics

Methods (1)

Keywords

regret bound (11) reinforcement learning (9) markov decision process (7) multi-armed bandit (4) optimal policy (4) online learning (4) upper confidence bound (3) sample complexity (3) continuous state space (2) non-stationary bandit (2) online reinforcement learning (2) dynamic regret (2) minimax regret (2) state representation (2) contextual bandit (2) side information (1) undiscounted setting (1) mutual information (1) exploration-exploitation (1) reinforcement learning theory (1)

Papers

Autonomous Exploration for Navigating in MDPs Using Blackbox RL Algorithms IJCAI 2023
Variational Regret Bounds for Reinforcement Learning UAI 2019
Regret Bounds for Learning State Representations in Reinforcement Learning NIPS 2019
Adaptively Tracking the Best Bandit Arm with an Unknown Number of Distribution Changes COLT 2019
Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information COLT 2019
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning ICML 2018
Pareto Front Identification from Stochastic Bandit Feedback AISTATS 2016
Improved Learning Complexity in Combinatorial Pure Exploration Bandits AISTATS 2016
Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning ICML 2015
Competing with an Infinite Set of Models in Reinforcement Learning AISTATS 2013
Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning ICML 2013
Online Regret Bounds for Undiscounted Continuous Reinforcement Learning NIPS 2012
PAC-Bayesian Analysis of Contextual Bandits NIPS 2011
Near-optimal Regret Bounds for Reinforcement Learning JMLR 2010
Near-optimal Regret Bounds for Reinforcement Learning NIPS 2008
Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning NIPS 2006