Aditya Gopalan

research

∙ 09/06/2023

A Unified Framework for Discovering Discrete Symmetries

We consider the problem of learning a function respecting a symmetry fro...

0 Pavan Karjol, et al. ∙

research

∙ 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...

0 Debangshu Banerjee, et al. ∙

research

∙ 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...

0 Debangshu Banerjee, et al. ∙

research

∙ 07/19/2022

Actor-Critic based Improper Reinforcement Learning

We consider an improper reinforcement learning setting where a learner i...

0 Mohammadi Zaki, et al. ∙

research

∙ 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...

0 Aditya Gopalan, et al. ∙

research

∙ 03/31/2022

Adaptive Estimation of Random Vectors with Bandit Feedback

We consider the problem of sequentially learning to estimate, in the mea...

0 Dipayan Sen, et al. ∙

research

∙ 01/18/2022

Bregman Deviations of Generic Exponential Families

We revisit the method of mixture technique, also known as the Laplace me...

0 Sayak Ray Chowdhury, et al. ∙

research

∙ 10/25/2021

On Slowly-varying Non-stationary Bandits

We consider minimisation of dynamic regret in non-stationary bandits wit...

0 Ramakrishnan Krishnamurthy, et al. ∙

research

∙ 10/18/2021

Data Flow Dissemination in a Network

We consider the following network model motivated, in particular, by blo...

0 Aditya Gopalan, et al. ∙

research

∙ 07/22/2021

Bandit Quickest Changepoint Detection

Detecting abrupt changes in temporal behavior patterns is of interest in...

0 Aditya Gopalan, et al. ∙

research

∙ 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...

0 Mohammani Zaki, et al. ∙

research

∙ 02/16/2021

Improper Learning with Gradient-based Policy Optimization

We consider an improper reinforcement learning setting where the learner...

0 Mohammadi Zaki, et al. ∙

research

∙ 11/02/2020

Stochastic Linear Bandits with Protected Subspace

We study a variant of the stochastic linear bandit problem wherein we op...

0 Advait Parulekar, et al. ∙

research

∙ 08/20/2020

No-regret Algorithms for Multi-task Bayesian Optimization

We consider multi-objective optimization (MOO) of an unknown vector-valu...

14 Sayak Ray Chowdhury, et al. ∙

research

∙ 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...

0 Gayathri R Prabhu, et al. ∙

research

∙ 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...

0 Mohammadi Zaki, et al. ∙

research

∙ 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...

0 Aditya Gopalan, et al. ∙

research

∙ 02/20/2020

Regret Minimization in Stochastic Contextual Dueling Bandits

We consider the problem of stochastic K-armed dueling bandit in the cont...

0 Aadirupa Saha, et al. ∙

research

∙ 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...

0 Avinash Mohan, et al. ∙

research

∙ 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...

0 Aadirupa Saha, et al. ∙

research

∙ 02/07/2020

Stability and Scalability of Blockchain Systems

The blockchain paradigm provides a mechanism for content dissemination a...

0 Aditya Gopalan, et al. ∙

research

∙ 11/19/2019

Sequential Mode Estimation with Oracle Queries

We consider the problem of adaptively PAC-learning a probability distrib...

0 Dhruti Shah, et al. ∙

research

∙ 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...

0 Mohammadi Zaki, et al. ∙

research

∙ 11/04/2019

On Online Learning in Kernelized Markov Decision Processes

We develop algorithms with low regret for learning episodic Markov decis...

0 Sayak Ray Chowdhury, et al. ∙

research

∙ 11/04/2019

On Batch Bayesian Optimization

We present two algorithms for Bayesian optimization in the batch feedbac...

0 Sayak Ray Chowdhury, et al. ∙

research

∙ 10/19/2019

On Adaptivity in Information-constrained Online Learning

We study how to adapt to smoothly-varying (`easy') environments in well-...

0 Siddharth Mitra, et al. ∙

research

∙ 09/16/2019

Bayesian Optimization under Heavy-tailed Payoffs

We consider black box optimization of an unknown function in the nonpara...

0 Sayak Ray Chowdhury, et al. ∙

research

∙ 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...

0 Aadirupa Saha, et al. ∙

research

∙ 03/01/2019

Regret Minimisation in Multinomial Logit Bandits

We consider two regret minimisation problems over subsets of a finite gr...

0 Aadirupa Saha, et al. ∙

research

∙ 10/23/2018

Active Ranking with Subset-wise Preferences

We consider the problem of probably approximately correct (PAC) ranking ...

0 Aadirupa Saha, et al. ∙

research

∙ 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...

0 Aditya Gopalan, et al. ∙

research

∙ 05/21/2018

Online Learning in Kernelized Markov Decision Processes

We consider online learning for minimizing regret in unknown, episodic M...

0 Sayak Ray Chowdhury, et al. ∙

research

∙ 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...

0 Gayathri R Prabhu, et al. ∙

research

∙ 02/29/2016

Collaborative Learning of Stochastic Bandits over a Social Network

We consider a collaborative online learning paradigm, wherein a group of...

0 Ravi Kumar Kolla, et al. ∙

research

∙ 06/29/2014

Thompson Sampling for Learning Parameterized Markov Decision Processes

We consider reinforcement learning in parameterized Markov Decision Proc...

0 Aditya Gopalan, et al. ∙

Aditya Gopalan

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