A Relative Exponential Weighing Algorithm for Adversarial Utility-based Dueling Bandits. - Pratik Gajane; Tanguy Urvoy; Fabrice Clérot (ICML, 2015)

Utility-based Dueling Bandits as a Partial Monitoring Game. - Pratik Gajane; Tanguy Urvoy (CoRR, 2015)

Corrupt Bandits for Privacy Preserving Input. - Pratik Gajane; Tanguy Urvoy; Emilie Kaufmann (CoRR, 2017)

On formalizing fairness in prediction with machine learning. - Pratik Gajane (CoRR, 2017)

Counterfactual Learning for Machine Translation: Degeneracies and Solutions. - Carolin Lawrence; Pratik Gajane; Stefan Riezler (CoRR, 2017)

Bandits Multi-bras avec retour d'information non-conventionnelle. (Multi-Armed Bandits with Unconventional Feedback). - Pratik Gajane (2017)

Corrupt Bandits for Preserving Local Privacy. - Pratik Gajane; Tanguy Urvoy; Emilie Kaufmann (ALT, 2018)

A Sliding-Window Algorithm for Markov Decision Processes with Arbitrarily Changing Rewards and Transitions. - Pratik Gajane; Ronald Ortner; Peter Auer (CoRR, 2018)

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 (COLT, 2019)

Variational Regret Bounds for Reinforcement Learning. - Ronald Ortner; Pratik Gajane; Peter Auer (UAI, 2019)

Autonomous exploration for navigating in non-stationary CMPs. - Pratik Gajane; Ronald Ortner; Peter Auer; Csaba Szepesvári (CoRR, 2019)

Gambler Bandits and the Regret of Being Ruined. - Filipo Studzinski Perotto; Sattar Vakili; Pratik Gajane; Yaser Faghan; Mathieu Bourgais (AAMAS, 2021)

The Impact of Batch Learning in Stochastic Bandits. - Danil Provodin; Pratik Gajane; Mykola Pechenizkiy; Maurits Kaptein (CoRR, 2021)

The Impact of Batch Learning in Stochastic Linear Bandits. - Danil Provodin; Pratik Gajane; Mykola Pechenizkiy; Maurits Kaptein (ICDM, 2022)

Survey on Fair Reinforcement Learning: Theory and Practice. - Pratik Gajane; Akrati Saxena; Maryam Tavakol; George Fletcher 001; Mykola Pechenizkiy (CoRR, 2022)

An Empirical Evaluation of Posterior Sampling for Constrained Reinforcement Learning. - Danil Provodin; Pratik Gajane; Mykola Pechenizkiy; Maurits Kaptein (CoRR, 2022)

Generalizing distribution of partial rewards for multi-armed bandits with temporally-partitioned rewards. - Ronald C. van den Broek; Rik Litjens; Tobias Sagis; Luc Siecker; Nina Verbeeke; Pratik Gajane (CoRR, 2022)

WeHeart: A Personalized Recommendation Device for Physical Activity Encouragement in Cardiac Rehabilitation. - Rosa Van Tuijn; Tianqin Lu; Emma Driesse; Koen Franken; Pratik Gajane; Emilia I. Barakova (HHAI, 2023)

LEMON: Alternative Sampling for More Faithful Explanation Through Local Surrogate Models. - Dennis Collaris; Pratik Gajane; Joost Jorritsma; Jarke J. van Wijk; Mykola Pechenizkiy (IDA, 2023)

Autonomous Exploration for Navigating in MDPs Using Blackbox RL Algorithms. - Pratik Gajane; Peter Auer; Ronald Ortner (IJCAI, 2023)

WeHeart: A Personalized Recommendation Device for Physical Activity Encouragement and Preventing "Cold Start" in Cardiac Rehabilitation. - Rosa Van Tuijn; Tianqin Lu; Emma Driesse; Koen Franken; Pratik Gajane; Emilia I. Barakova (INTERACT (3), 2023)

Local Differential Privacy for Sequential Decision Making in a Changing Environment. - Pratik Gajane (CoRR, 2023)

Curiosity-driven Exploration in Sparse-reward Multi-agent Reinforcement Learning. - Jiong Li; Pratik Gajane (CoRR, 2023)

Multi-Armed Bandits with Generalized Temporally-Partitioned Rewards. - Ronald C. van den Broek; Rik Litjens; Tobias Sagis; Luc Siecker; Nina Verbeeke; Pratik Gajane (CoRR, 2023)

Provably Efficient Exploration in Constrained Reinforcement Learning: Posterior Sampling Is All You Need. - Danil Provodin; Pratik Gajane; Mykola Pechenizkiy; Maurits Kaptein (CoRR, 2023)

Multi-armed Bandits with Generalized Temporally-Partitioned Rewards. - Ronald C. van den Broek; Rik Litjens; Tobias Sagis; Nina Verbeeke; Pratik Gajane (IDA (1), 2024)

Investigating Gender Fairness in Machine Learning-driven Personalized Care for Chronic Pain. - Pratik Gajane; Sean Newman; John D. Piette (CoRR, 2024)

Adversarial Multi-dueling Bandits. - Pratik Gajane (CoRR, 2024)