Arnak S. Dalalyan | DeepAI

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∙ 04/07/2023

Graphon Estimation in bipartite graphs with observable edge labels and unobservable node labels

Many real-world data sets can be presented in the form of a matrix whose...

0 Etienne Donier-Meroz, et al. ∙

∙ 12/25/2022

Simple proof of the risk bound for denoising by exponential weights for asymmetric noise distributions

In this note, we consider the problem of aggregation of estimators in or...

0 Arnak S. Dalalyan, et al. ∙

∙ 04/05/2022

Nearly minimax robust estimator of the mean vector by iterative spectral dimension reduction

We study the problem of robust estimation of the mean vector of a sub-Ga...

0 Amir-Hossein Bateni, et al. ∙

∙ 12/21/2021

Risk bounds for aggregated shallow neural networks using Gaussian prior

Analysing statistical properties of neural networks is a central topic i...

0 Laura Tinsi, et al. ∙

∙ 06/24/2020

Penalized Langevin dynamics with vanishing penalty for smooth and log-concave targets

We study the problem of sampling from a probability distribution on ℝ^p ...

0 Avetik Karagulyan, et al. ∙

∙ 02/04/2020

All-In-One Robust Estimator of the Gaussian Mean

The goal of this paper is to show that a single robust estimator of the ...

0 Arnak S. Dalalyan, et al. ∙

∙ 06/20/2019

Bounding the error of discretized Langevin algorithms for non-strongly log-concave targets

In this paper, we provide non-asymptotic upper bounds on the error of sa...

0 Arnak S. Dalalyan, et al. ∙

∙ 04/12/2019

Outlier-robust estimation of a sparse linear model using ℓ_1-penalized Huber's M-estimator

We study the problem of estimating a p-dimensional s-sparse vector in a ...

0 Arnak S. Dalalyan, et al. ∙

∙ 03/15/2019

A nonasymptotic law of iterated logarithm for robust online estimators

In this paper, we provide tight deviation bounds for M-estimators, which...

0 Victor-Emmanuel Brunel, et al. ∙

∙ 02/12/2019

Minimax rates in outlier-robust estimation of discrete models

We consider the problem of estimating the probability distribution of a ...

0 Amir-Hossein Bateni, et al. ∙

∙ 07/24/2018

On sampling from a log-concave density using kinetic Langevin diffusions

Langevin diffusion processes and their discretizations are often used fo...

0 Arnak S. Dalalyan, et al. ∙

∙ 06/25/2018

Exponential weights in multivariate regression and a low-rankness favoring prior

We establish theoretical guarantees for the expected prediction error of...

0 Arnak S. Dalalyan, et al. ∙

∙ 12/15/2017

Rate-optimal estimation of p-dimensional linear functionals in a sparse Gaussian model

We consider two problems of estimation in high-dimensional Gaussian mode...

0 Olivier Collier, et al. ∙

∙ 09/29/2017

User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient

In this paper, we revisit the recently established theoretical guarantee...

0 Arnak S. Dalalyan, et al. ∙

∙ 06/20/2016

On the prediction loss of the lasso in the partially labeled setting

In this paper we revisit the risk bounds of the lasso estimator in the c...

0 Pierre C. Bellec, et al. ∙

∙ 12/23/2014

Theoretical guarantees for approximate sampling from smooth and log-concave densities

Sampling from various kinds of distributions is an issue of paramount im...

0 Arnak S. Dalalyan, et al. ∙

∙ 02/07/2014

On the Prediction Performance of the Lasso

Although the Lasso has been extensively studied, the relationship betwee...

0 Arnak S. Dalalyan, et al. ∙

∙ 04/16/2013

Learning Heteroscedastic Models by Convex Programming under Group Sparsity

Popular sparse estimation methods based on ℓ_1-relaxation, such as the L...

0 Arnak S. Dalalyan, et al. ∙

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