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07/04/2023
Online Learning and Solving Infinite Games with an ERM Oracle
While ERM suffices to attain near-optimal generalization error in the st...
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05/30/2023
Ambient Diffusion: Learning Clean Distributions from Corrupted Data
We present the first diffusion-based framework that can learn an unknown...
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02/17/2023
Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent
Imperfect score-matching leads to a shift between the training and the s...
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11/23/2022
Learning and Testing Latent-Tree Ising Models Efficiently
We provide time- and sample-efficient algorithms for learning and testin...
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11/21/2022
EM's Convergence in Gaussian Latent Tree Models
We study the optimization landscape of the log-likelihood function and t...
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06/18/2022
Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems
We prove fast mixing and characterize the stationary distribution of the...
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02/09/2022
Smoothed Online Learning is as Easy as Statistical Learning
Much of modern learning theory has been split between two regimes: the c...
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07/20/2021
Statistical Estimation from Dependent Data
We consider a general statistical estimation problem wherein binary labe...
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02/02/2021
Majorizing Measures, Sequential Complexities, and Online Learning
We introduce the technique of generic chaining and majorizing measures f...
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01/22/2021
Adversarial Laws of Large Numbers and Optimal Regret in Online Classification
Laws of large numbers guarantee that given a large enough sample from so...
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12/07/2020
A bounded-noise mechanism for differential privacy
Answering multiple counting queries is one of the best-studied problems ...
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04/20/2020
Estimating Ising Models from One Sample
Given one sample X ∈{± 1}^n from an Ising model [X=x]∝(x^ J x/2), whose ...
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11/24/2019
PAC learning with stable and private predictions
We study binary classification algorithms for which the prediction on an...
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11/11/2019
Interaction is necessary for distributed learning with privacy or communication constraints
Local differential privacy (LDP) is a model where users send privatized ...
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06/21/2019
Learning from weakly dependent data under Dobrushin's condition
Statistical learning theory has largely focused on learning and generali...
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03/13/2019
The Log-Concave Maximum Likelihood Estimator is Optimal in High Dimensions
We study the problem of learning a d-dimensional log-concave distributio...
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02/09/2019
Space lower bounds for linear prediction
We show that fundamental learning tasks, such as finding an approximate ...
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11/06/2018
The entropy of lies: playing twenty questions with a liar
`Twenty questions' is a guessing game played by two players: Bob thinks ...
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03/28/2018
A Better Resource Allocation Algorithm with Semi-Bandit Feedback
We study a sequential resource allocation problem between a fixed number...
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03/04/2018