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08/23/2023
On Uniformly Optimal Algorithms for Best Arm Identification in Two-Armed Bandits with Fixed Budget
We study the problem of best-arm identification with fixed budget in sto...
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06/18/2023
Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model
We consider the problem of recovering hidden communities in the Labeled ...
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04/05/2023
Conformal Off-Policy Evaluation in Markov Decision Processes
Reinforcement Learning aims at identifying and evaluating efficient cont...
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11/28/2022
On the Sample Complexity of Representation Learning in Multi-task Bandits with Global and Local structure
We investigate the sample complexity of learning the optimal arm for mul...
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11/16/2022
Analysis and Detectability of Offline Data Poisoning Attacks on Linear Systems
A recent body of literature has investigated the effect of data poisonin...
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08/17/2022
Nearly Optimal Latent State Decoding in Block MDPs
We investigate the problems of model estimation and reward-free learning...
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08/11/2022
Best Policy Identification in Linear MDPs
We investigate the problem of best policy identification in discounted l...
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04/14/2022
Measurement-based Admission Control in Sliced Networks: A Best Arm Identification Approach
In sliced networks, the shared tenancy of slices requires adaptive admis...
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01/06/2022
Learning Optimal Antenna Tilt Control Policies: A Contextual Linear Bandit Approach
Controlling antenna tilts in cellular networks is imperative to reach an...
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09/29/2021
Minimal Expected Regret in Linear Quadratic Control
We consider the problem of online learning in Linear Quadratic Control s...
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09/15/2021
Balancing detectability and performance of attacks on the control channel of Markov Decision Processes
We investigate the problem of designing optimal stealthy poisoning attac...
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09/13/2021
Online Learning of Optimally Diverse Rankings
Search engines answer users' queries by listing relevant items (e.g. doc...
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06/27/2021
Regret Analysis in Deterministic Reinforcement Learning
We consider Markov Decision Processes (MDPs) with deterministic transiti...
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06/05/2021
Navigating to the Best Policy in Markov Decision Processes
We investigate the classical active pure exploration problem in Markov D...
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10/23/2020
Regret in Online Recommendation Systems
This paper proposes a theoretical analysis of recommendation systems in ...
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10/22/2020
Thresholded LASSO Bandit
In this paper, we revisit sparse stochastic contextual linear bandits. I...
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09/28/2020
Best Policy Identification in discounted MDPs: Problem-specific Sample Complexity
We investigate the problem of best-policy identification in discounted M...
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06/29/2020
Optimal Best-arm Identification in Linear Bandits
We study the problem of best-arm identification with fixed confidence in...
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05/21/2020
Off-policy Learning for Remote Electrical Tilt Optimization
We address the problem of Remote Electrical Tilt (RET) optimization usin...
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04/02/2020
Predictive Bandits
We introduce and study a new class of stochastic bandit problems, referr...
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03/17/2020
Finite-time Identification of Stable Linear Systems: Optimality of the Least-Squares Estimator
We provide a new finite-time analysis of the estimation error of stable ...
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12/20/2019
Distributed Online Optimization with Long-Term Constraints
We consider distributed online convex optimization problems, where the d...
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10/14/2019
Optimal Clustering from Noisy Binary Feedback
We study the problem of recovering clusters from binary user feedback. I...
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09/28/2019
An Optimal Algorithm in Multiplayer Multi-Armed Bandits
The paper addresses the Multiplayer Multi-Armed Bandit (MMAB) problem, w...
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07/31/2019
Optimal Attacks on Reinforcement Learning Policies
Control policies, trained using the Deep Reinforcement Learning, have be...
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06/27/2019
From self-tuning regulators to reinforcement learning and back again
Machine and reinforcement learning (RL) are being applied to plan and co...
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03/25/2019
Sample Complexity Lower Bounds for Linear System Identification
This paper establishes problem-specific sample complexity lower bounds f...
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02/13/2019
Distributed Online Linear Regression
We study online linear regression problems in a distributed setting, whe...
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07/02/2018
Appearance-Based 3D Gaze Estimation with Personal Calibration
We propose a way to incorporate personal calibration into a deep learnin...
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06/03/2018
Exploration in Structured Reinforcement Learning
We address reinforcement learning problems with finite state and action ...
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11/01/2017
Minimal Exploration in Structured Stochastic Bandits
This paper introduces and addresses a wide class of stochastic bandit pr...
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10/20/2015
Optimal Cluster Recovery in the Labeled Stochastic Block Model
We consider the problem of community detection or clustering in the labe...
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04/13/2015
Streaming, Memory Limited Matrix Completion with Noise
In this paper, we consider the streaming memory-limited matrix completio...
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02/11/2015
Combinatorial Bandits Revisited
This paper investigates stochastic and adversarial combinatorial multi-a...
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05/20/2014
