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09/06/2023
A Unified Framework for Discovering Discrete Symmetries
We consider the problem of learning a function respecting a symmetry fro...
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01/09/2023
On the Minimax Regret for Linear Bandits in a wide variety of Action Spaces
As noted in the works of <cit.>, it has been mentioned that it is an ope...
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07/23/2022
Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference
We present a non-asymptotic lower bound on the eigenspectrum of the desi...
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07/19/2022
Actor-Critic based Improper Reinforcement Learning
We consider an improper reinforcement learning setting where a learner i...
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05/26/2022
Approximate Q-learning and SARSA(0) under the ε-greedy Policy: a Differential Inclusion Analysis
Q-learning and SARSA(0) with linear function approximation, under ϵ-gree...
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03/31/2022
Adaptive Estimation of Random Vectors with Bandit Feedback
We consider the problem of sequentially learning to estimate, in the mea...
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01/18/2022
Bregman Deviations of Generic Exponential Families
We revisit the method of mixture technique, also known as the Laplace me...
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10/25/2021
On Slowly-varying Non-stationary Bandits
We consider minimisation of dynamic regret in non-stationary bandits wit...
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10/18/2021
Data Flow Dissemination in a Network
We consider the following network model motivated, in particular, by blo...
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07/22/2021
Bandit Quickest Changepoint Detection
Detecting abrupt changes in temporal behavior patterns is of interest in...
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05/01/2021
Better than the Best: Gradient-based Improper Reinforcement Learning for Network Scheduling
We consider the problem of scheduling in constrained queueing networks w...
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02/16/2021
Improper Learning with Gradient-based Policy Optimization
We consider an improper reinforcement learning setting where the learner...
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11/02/2020
Stochastic Linear Bandits with Protected Subspace
We study a variant of the stochastic linear bandit problem wherein we op...
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08/20/2020
No-regret Algorithms for Multi-task Bayesian Optimization
We consider multi-objective optimization (MOO) of an unknown vector-valu...
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07/25/2020
Sequential Multi-hypothesis Testing in Multi-armed Bandit Problems:An Approach for Asymptotic Optimality
We consider a multi-hypothesis testing problem involving a K-armed bandi...
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06/13/2020
Explicit Best Arm Identification in Linear Bandits Using No-Regret Learners
We study the problem of best arm identification in linearly parameterise...
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04/24/2020
How Reliable are Test Numbers for Revealing the COVID-19 Ground Truth and Applying Interventions?
The number of confirmed cases of COVID-19 is often used as a proxy for t...
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02/20/2020
Regret Minimization in Stochastic Contextual Dueling Bandits
We consider the problem of stochastic K-armed dueling bandit in the cont...
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02/19/2020
Throughput Optimal Decentralized Scheduling with Single-bit State Feedback for a Class of Queueing Systems
Motivated by medium access control for resource-challenged wireless Inte...
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02/19/2020
Best-item Learning in Random Utility Models with Subset Choices
We consider the problem of PAC learning the most valuable item from a po...
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02/07/2020
Stability and Scalability of Blockchain Systems
The blockchain paradigm provides a mechanism for content dissemination a...
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11/19/2019
Sequential Mode Estimation with Oracle Queries
We consider the problem of adaptively PAC-learning a probability distrib...
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11/05/2019
Towards Optimal and Efficient Best Arm Identification in Linear Bandits
We give a new algorithm for best arm identification in linearly paramete...
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11/04/2019
On Online Learning in Kernelized Markov Decision Processes
We develop algorithms with low regret for learning episodic Markov decis...
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11/04/2019
On Batch Bayesian Optimization
We present two algorithms for Bayesian optimization in the batch feedbac...
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10/19/2019
On Adaptivity in Information-constrained Online Learning
We study how to adapt to smoothly-varying (`easy') environments in well-...
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09/16/2019
Bayesian Optimization under Heavy-tailed Payoffs
We consider black box optimization of an unknown function in the nonpara...
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03/01/2019
From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model
We consider PAC learning for identifying a good item from subset-wise sa...
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03/01/2019
Regret Minimisation in Multinomial Logit Bandits
We consider two regret minimisation problems over subsets of a finite gr...
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10/23/2018
Active Ranking with Subset-wise Preferences
We consider the problem of probably approximately correct (PAC) ranking ...
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08/12/2018
PAC-Battling Bandits with Plackett-Luce: Tradeoff between Sample Complexity and Subset Size
We introduce the probably approximately correct (PAC) version of the pro...
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05/21/2018
Online Learning in Kernelized Markov Decision Processes
We consider online learning for minimizing regret in unknown, episodic M...
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12/11/2017
Optimal Odd Arm Identification with Fixed Confidence
The problem of detecting an odd arm from a set of K arms of a multi-arme...
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02/29/2016
Collaborative Learning of Stochastic Bandits over a Social Network
We consider a collaborative online learning paradigm, wherein a group of...
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06/29/2014