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09/08/2023
Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning
We introduce a new type of query mechanism for collecting human feedback...
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07/25/2023
Do algorithms and barriers for sparse principal component analysis extend to other structured settings?
We study a principal component analysis problem under the spiked Wishart...
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02/20/2023
Sharp analysis of EM for learning mixtures of pairwise differences
We consider a symmetric mixture of linear regressions with random sample...
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07/23/2022
A Dual Accelerated Method for Online Stochastic Distributed Averaging: From Consensus to Decentralized Policy Evaluation
Motivated by decentralized sensing and policy evaluation problems, we co...
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07/20/2022
Alternating minimization for generalized rank one matrix sensing: Sharp predictions from a random initialization
We consider the problem of estimating the factors of a rank-1 matrix wit...
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05/03/2022
Modeling and Correcting Bias in Sequential Evaluation
We consider the problem of sequential evaluation, in which an evaluator ...
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12/24/2021
Accelerated and instance-optimal policy evaluation with linear function approximation
We study the problem of policy evaluation with linear function approxima...
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12/23/2021
Optimal and instance-dependent guarantees for Markovian linear stochastic approximation
We study stochastic approximation procedures for approximately solving a...
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09/20/2021
Sharp global convergence guarantees for iterative nonconvex optimization: A Gaussian process perspective
We consider a general class of regression models with normally distribut...
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06/28/2021
Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits
We introduce the "inverse bandit" problem of estimating the rewards of a...
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05/05/2021
Preference learning along multiple criteria: A game-theoretic perspective
The literature on ranking from ordinal data is vast, and there are sever...
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12/09/2020
Optimal oracle inequalities for solving projected fixed-point equations
Linear fixed point equations in Hilbert spaces arise in a variety of set...
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09/05/2020
Isotonic regression with unknown permutations: Statistics, computation, and adaptation
Motivated by models for multiway comparison data, we consider the proble...
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03/16/2020
Is Temporal Difference Learning Optimal? An Instance-Dependent Analysis
We address the problem of policy evaluation in discounted Markov decisio...
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09/19/2019
Value function estimation in Markov reward processes: Instance-dependent ℓ_∞-bounds for policy evaluation
Markov reward processes (MRPs) are used to model stochastic phenomena ar...
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06/21/2019
Max-Affine Regression: Provable, Tractable, and Near-Optimal Statistical Estimation
Max-affine regression refers to a model where the unknown regression fun...
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02/22/2019
A Family of Bayesian Cramér-Rao Bounds, and Consequences for Log-Concave Priors
Under minimal regularity assumptions, we establish a family of informati...
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12/20/2018
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems
We study derivative-free methods for policy optimization over the class ...
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06/25/2018
Towards Optimal Estimation of Bivariate Isotonic Matrices with Unknown Permutations
Many applications, including rank aggregation, crowd-labeling, and graph...
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02/27/2018
Breaking the 1/√(n) Barrier: Faster Rates for Permutation-based Models in Polynomial Time
Many applications, including rank aggregation and crowd-labeling, can be...
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07/19/2017
Worst-case vs Average-case Design for Estimation from Fixed Pairwise Comparisons
Pairwise comparison data arises in many domains, including tournament ra...
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04/24/2017
Denoising Linear Models with Permuted Data
The multivariate linear regression model with shuffled data and additive...
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08/09/2016