Yuval Dagan | DeepAI

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Alexander Rakhlin
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Constantinos Daskalakis
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Vitaly Feldman
41 publications
Noga Alon
35 publications
Noah Golowich
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Surbhi Goel
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Yuval Filmus
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Omri Ben-Eliezer
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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...

0 Angelos Assos, et al. ∙

∙ 05/30/2023

Ambient Diffusion: Learning Clean Distributions from Corrupted Data

We present the first diffusion-based framework that can learn an unknown...

0 Giannis Daras, et al. ∙

∙ 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...

0 Giannis Daras, et al. ∙

∙ 11/23/2022

Learning and Testing Latent-Tree Ising Models Efficiently

We provide time- and sample-efficient algorithms for learning and testin...

0 Davin Choo, et al. ∙

∙ 11/21/2022

EM's Convergence in Gaussian Latent Tree Models

We study the optimization landscape of the log-likelihood function and t...

0 Yuval Dagan, et al. ∙

∙ 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...

7 Giannis Daras, et al. ∙

∙ 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...

0 Adam Block, et al. ∙

∙ 07/20/2021

Statistical Estimation from Dependent Data

We consider a general statistical estimation problem wherein binary labe...

0 Yuval Dagan, et al. ∙

∙ 02/02/2021

Majorizing Measures, Sequential Complexities, and Online Learning

We introduce the technique of generic chaining and majorizing measures f...

0 Adam Block, et al. ∙

∙ 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...

6 Noga Alon, et al. ∙

∙ 12/07/2020

A bounded-noise mechanism for differential privacy

Answering multiple counting queries is one of the best-studied problems ...

0 Yuval Dagan, et al. ∙

∙ 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 ...

0 Yuval Dagan, et al. ∙

∙ 11/24/2019

PAC learning with stable and private predictions

We study binary classification algorithms for which the prediction on an...

10 Yuval Dagan, et al. ∙

∙ 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 ...

10 Yuval Dagan, et al. ∙

∙ 06/21/2019

Learning from weakly dependent data under Dobrushin's condition

Statistical learning theory has largely focused on learning and generali...

0 Yuval Dagan, et al. ∙

∙ 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...

0 Yuval Dagan, et al. ∙

∙ 02/09/2019

Space lower bounds for linear prediction

We show that fundamental learning tasks, such as finding an approximate ...

0 Yuval Dagan, et al. ∙

∙ 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 ...

0 Yuval Dagan, et al. ∙

∙ 03/28/2018

A Better Resource Allocation Algorithm with Semi-Bandit Feedback

We study a sequential resource allocation problem between a fixed number...

0 Yuval Dagan, et al. ∙

∙ 03/04/2018

Detecting Correlations with Little Memory and Communication

We study the problem of identifying correlations in multivariate data, u...

0 Yuval Dagan, et al. ∙

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