Pratik Gajane | DeepAI

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∙ 03/01/2023

Multi-Armed Bandits with Generalized Temporally-Partitioned Rewards

Decision-making problems of sequential nature, where decisions made in t...

0 Ronald C. van den Broek, et al. ∙

∙ 02/21/2023

Curiosity-driven Exploration in Sparse-reward Multi-agent Reinforcement Learning

Sparsity of rewards while applying a deep reinforcement learning method ...

0 Jiong Li, et al. ∙

∙ 01/02/2023

Local Differential Privacy for Sequential Decision Making in a Changing Environment

We study the problem of preserving privacy while still providing high ut...

0 Pratik Gajane, et al. ∙

∙ 11/13/2022

Generalizing distribution of partial rewards for multi-armed bandits with temporally-partitioned rewards

We investigate the Multi-Armed Bandit problem with Temporally-Partitione...

0 Ronald C. van den Broek, et al. ∙

∙ 09/08/2022

An Empirical Evaluation of Posterior Sampling for Constrained Reinforcement Learning

We study a posterior sampling approach to efficient exploration in const...

6 Danil Provodin, et al. ∙

∙ 05/20/2022

Survey on Fair Reinforcement Learning: Theory and Practice

Fairness-aware learning aims at satisfying various fairness constraints ...

49 Pratik Gajane, et al. ∙

∙ 02/14/2022

The Impact of Batch Learning in Stochastic Linear Bandits

We consider a special case of bandit problems, named batched bandits, in...

0 Danil Provodin, et al. ∙

∙ 11/03/2021

The Impact of Batch Learning in Stochastic Bandits

We consider a special case of bandit problems, namely batched bandits. M...

12 Danil Provodin, et al. ∙

∙ 10/18/2019

Autonomous exploration for navigating in non-stationary CMPs

We consider a setting in which the objective is to learn to navigate in ...

10 Pratik Gajane, et al. ∙

∙ 05/14/2019

Variational Regret Bounds for Reinforcement Learning

We consider undiscounted reinforcement learning in Markov decision proce...

0 Pratik Gajane, et al. ∙

∙ 05/25/2018

A Sliding-Window Algorithm for Markov Decision Processes with Arbitrarily Changing Rewards and Transitions

We consider reinforcement learning in changing Markov Decision Processes...

0 Pratik Gajane, et al. ∙

∙ 11/23/2017

Counterfactual Learning for Machine Translation: Degeneracies and Solutions

Counterfactual learning is a natural scenario to improve web-based machi...

0 Carolin Lawrence, et al. ∙

∙ 10/09/2017

On formalizing fairness in prediction with machine learning

Machine learning algorithms for prediction are increasingly being used i...

0 Pratik Gajane, et al. ∙

∙ 08/16/2017

Corrupt Bandits for Preserving Local Privacy

We study a variant of the stochastic multi-armed bandit (MAB) problem in...

0 Pratik Gajane, et al. ∙

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