Pratik Gajane

Orcid: 0000-0002-8087-5661

According to our database1, Pratik Gajane authored at least 28 papers between 2015 and 2024.

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Bibliography

2024
Investigating Gender Fairness in Machine Learning-driven Personalized Care for Chronic Pain.
CoRR, 2024

Multi-armed Bandits with Generalized Temporally-Partitioned Rewards.
Proceedings of the Advances in Intelligent Data Analysis XXII, 2024

2023
Provably Efficient Exploration in Constrained Reinforcement Learning: Posterior Sampling Is All You Need.
CoRR, 2023

Multi-Armed Bandits with Generalized Temporally-Partitioned Rewards.
CoRR, 2023

Curiosity-driven Exploration in Sparse-reward Multi-agent Reinforcement Learning.
CoRR, 2023

Local Differential Privacy for Sequential Decision Making in a Changing Environment.
CoRR, 2023

WeHeart: A Personalized Recommendation Device for Physical Activity Encouragement and Preventing "Cold Start" in Cardiac Rehabilitation.
Proceedings of the Human-Computer Interaction - INTERACT 2023 - 19th IFIP TC13 International Conference, York, UK, August 28, 2023

Autonomous Exploration for Navigating in MDPs Using Blackbox RL Algorithms.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

LEMON: Alternative Sampling for More Faithful Explanation Through Local Surrogate Models.
Proceedings of the Advances in Intelligent Data Analysis XXI, 2023

WeHeart: A Personalized Recommendation Device for Physical Activity Encouragement in Cardiac Rehabilitation.
Proceedings of the HHAI 2023: Augmenting Human Intellect, 2023

2022
Generalizing distribution of partial rewards for multi-armed bandits with temporally-partitioned rewards.
CoRR, 2022

An Empirical Evaluation of Posterior Sampling for Constrained Reinforcement Learning.
CoRR, 2022

Survey on Fair Reinforcement Learning: Theory and Practice.
CoRR, 2022

The Impact of Batch Learning in Stochastic Linear Bandits.
Proceedings of the IEEE International Conference on Data Mining, 2022

2021
The Impact of Batch Learning in Stochastic Bandits.
CoRR, 2021

Gambler Bandits and the Regret of Being Ruined.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2019
Autonomous exploration for navigating in non-stationary CMPs.
CoRR, 2019

Variational Regret Bounds for Reinforcement Learning.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Adaptively Tracking the Best Bandit Arm with an Unknown Number of Distribution Changes.
Proceedings of the Conference on Learning Theory, 2019

Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information.
Proceedings of the Conference on Learning Theory, 2019

2018
A Sliding-Window Algorithm for Markov Decision Processes with Arbitrarily Changing Rewards and Transitions.
CoRR, 2018

Corrupt Bandits for Preserving Local Privacy.
Proceedings of the Algorithmic Learning Theory, 2018

2017
Bandits Multi-bras avec retour d'information non-conventionnelle. (Multi-Armed Bandits with Unconventional Feedback).
PhD thesis, 2017

Counterfactual Learning for Machine Translation: Degeneracies and Solutions.
CoRR, 2017

On formalizing fairness in prediction with machine learning.
CoRR, 2017

Corrupt Bandits for Privacy Preserving Input.
CoRR, 2017

2015
Utility-based Dueling Bandits as a Partial Monitoring Game.
CoRR, 2015

A Relative Exponential Weighing Algorithm for Adversarial Utility-based Dueling Bandits.
Proceedings of the 32nd International Conference on Machine Learning, 2015


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