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09/05/2023
On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence
Best Arm Identification (BAI) problems are progressively used for data-s...
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09/01/2023
Interactive and Concentrated Differential Privacy for Bandits
Bandits play a crucial role in interactive learning schemes and modern r...
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06/22/2023
Pure Exploration in Bandits with Linear Constraints
We address the problem of identifying the optimal policy with a fixed co...
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02/24/2023
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning
We study differentially private (DP) machine learning algorithms as inst...
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02/18/2023
Online Instrumental Variable Regression: Regret Analysis and Bandit Feedback
The independence of noise and covariates is a standard assumption in onl...
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02/16/2023
Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack using Public Data
We study black-box model stealing attacks where the attacker can query a...
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10/05/2022
Bilinear Exponential Family of MDPs: Frequentist Regret Bound with Tractable Exploration and Planning
We study the problem of episodic reinforcement learning in continuous st...
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09/06/2022
When Privacy Meets Partial Information: A Refined Analysis of Differentially Private Bandits
We study the problem of multi-armed bandits with ϵ-global Differential P...
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06/01/2022
How Biased is Your Feature?: Computing Fairness Influence Functions with Global Sensitivity Analysis
Fairness in machine learning has attained significant focus due to the w...
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04/20/2022
SAAC: Safe Reinforcement Learning as an Adversarial Game of Actor-Critics
Although Reinforcement Learning (RL) is effective for sequential decisio...
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03/07/2022
Bandits Corrupted by Nature: Lower Bounds on Regret and Robust Optimistic Algorithm
In this paper, we study the stochastic bandits problem with k unknown he...
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10/14/2021
Procrastinated Tree Search: Black-box Optimization with Delayed, Noisy, and Multi-fidelity Feedback
In black-box optimization problems, we aim to maximize an unknown object...
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09/20/2021
Algorithmic Fairness Verification with Graphical Models
In recent years, machine learning (ML) algorithms have been deployed in ...
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04/05/2021
UDO: Universal Database Optimization using Reinforcement Learning
UDO is a versatile tool for offline tuning of database systems for speci...
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09/25/2020
ε-net Induced Lazy Witness Complexes on Graphs
Computation of persistent homology of simplicial representations such as...
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09/14/2020
Justicia: A Stochastic SAT Approach to Formally Verify Fairness
As a technology ML is oblivious to societal good or bad, and thus, the f...
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04/11/2020
Construction and Random Generation of Hypergraphs with Prescribed Degree and Dimension Sequences
We propose algorithms for construction and random generation of hypergra...
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03/02/2020
Differential Privacy at Risk: Bridging Randomness and Privacy Budget
The calibration of noise for a privacy-preserving mechanism depends on t...
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02/08/2020
Inferential Induction: Joint Bayesian Estimation of MDPs and Value Functions
Bayesian reinforcement learning (BRL) offers a decision-theoretic soluti...
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06/20/2019
Near-optimal Bayesian Solution For Unknown Discrete Markov Decision Process
We tackle the problem of acting in an unknown finite and discrete Markov...
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06/20/2019
Near-optimal Reinforcement Learning using Bayesian Quantiles
We study model-based reinforcement learning in finite communicating Mark...
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06/14/2019
Topological Data Analysis with ε-net Induced Lazy Witness Complex
Topological data analysis computes and analyses topological features of ...
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05/29/2019
Differential Privacy for Multi-armed Bandits: What Is It and What Is Its Cost?
We introduce a number of privacy definitions for the multi-armed bandit ...
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05/27/2019
Near-optimal Optimistic Reinforcement Learning using Empirical Bernstein Inequalities
We study model-based reinforcement learning in an unknown finite communi...
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05/04/2018