Laurent Massoulie

research

∙ 07/10/2023

Generalization Error of First-Order Methods for Statistical Learning with Generic Oracles

In this paper, we provide a novel framework for the analysis of generali...

0 Kevin Scaman, et al. ∙

research

∙ 01/30/2023

Breadth-First Depth-Next: Optimal Collaborative Exploration of Trees with Low Diameter

We consider the problem of collaborative tree exploration posed by Fraig...

0 Romain Cosson, et al. ∙

research

∙ 09/27/2022

Statistical limits of correlation detection in trees

In this paper we address the problem of testing whether two observed tre...

0 Luca Ganassali, et al. ∙

research

∙ 06/10/2022

Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging

Decentralized optimization is increasingly popular in machine learning f...

0 Edwige Cyffers, et al. ∙

research

∙ 07/15/2021

Correlation detection in trees for partial graph alignment

Motivated by alignment of correlated sparse random graphs, we study a hy...

0 Luca Ganassali, et al. ∙

research

∙ 06/10/2021

A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip

We introduce the continuized Nesterov acceleration, a close variant of N...

0 Mathieu Even, et al. ∙

research

∙ 06/07/2021

Decentralized Optimization with Heterogeneous Delays: a Continuous-Time Approach

In decentralized optimization, nodes of a communication network privatel...

0 Mathieu Even, et al. ∙

research

∙ 02/04/2021

Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization

Dimension is an inherent bottleneck to some modern learning tasks, where...

0 Mathieu Even, et al. ∙

research

∙ 02/04/2021

Impossibility of Partial Recovery in the Graph Alignment Problem

Random graph alignment refers to recovering the underlying vertex corres...

0 Luca Ganassali, et al. ∙

research

∙ 11/04/2020

Asynchrony and Acceleration in Gossip Algorithms

This paper considers the minimization of a sum of smooth and strongly co...

0 Mathieu Even, et al. ∙

research

∙ 07/01/2020

Partial Recovery in the Graph Alignment Problem

In this paper, we consider the graph alignment problem, which is the pro...

0 Georgina Hall, et al. ∙

research

∙ 06/25/2020

Dual-Free Stochastic Decentralized Optimization with Variance Reduction

We consider the problem of training machine learning models on distribut...

0 Hadrien Hendrikx, et al. ∙

research

∙ 05/28/2020

Understanding and monitoring the local progression of the Covid-19 epidemic from medical emergency calls: the example of the Paris area

We portray the evolution of the Covid-19 epidemic during the crisis of M...

0 Stéphane Gaubert, et al. ∙

research

∙ 05/28/2020

Forecasting the local progression of the Covid-19 epidemic from medical emergency calls: the example of the Paris area

We portray the evolution of the Covid-19 epidemic during the crisis of M...

0 Stéphane Gaubert, et al. ∙

research

∙ 05/20/2020

An Optimal Algorithm for Decentralized Finite Sum Optimization

Modern large-scale finite-sum optimization relies on two key aspects: di...

0 Hadrien Hendrikx, et al. ∙

research

∙ 02/25/2020

Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization

We consider the setting of distributed empirical risk minimization where...

0 Hadrien Hendrikx, et al. ∙

research

∙ 02/04/2020

From tree matching to sparse graph alignment

In this paper we consider alignment of sparse graphs, for which we intro...

0 Luca Ganassali, et al. ∙

research

∙ 05/27/2019

An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums

Modern large-scale finite-sum optimization relies on two key aspects: di...

0 Hadrien Hendrikx, et al. ∙

research

∙ 01/28/2019

Asynchronous Accelerated Proximal Stochastic Gradient for Strongly Convex Distributed Finite Sums

In this work, we study the problem of minimizing the sum of strongly con...

0 Hadrien Hendrikx, et al. ∙

research

∙ 11/14/2018

Robustness of spectral methods for community detection

The present work is concerned with community detection. Specifically, we...

0 Ludovic Stephan, et al. ∙

research

∙ 10/05/2018

Accelerated Decentralized Optimization with Local Updates for Smooth and Strongly Convex Objectives

In this paper, we study the problem of minimizing a sum of smooth and st...

0 Hadrien Hendrikx, et al. ∙

research

∙ 06/20/2018

Efficient inference in stochastic block models with vertex labels

We study the stochastic block model with two communities where vertices ...

0 Clara Stegehuis, et al. ∙

research

∙ 03/02/2017

Adaptive Matching for Expert Systems with Uncertain Task Types

Online two-sided matching markets such as Q&A forums (e.g. StackOverflow...

0 Virag Shah, et al. ∙

research

∙ 02/28/2017

Optimal algorithms for smooth and strongly convex distributed optimization in networks

In this paper, we determine the optimal convergence rates for strongly c...

0 Kevin Scaman, et al. ∙

research

∙ 09/08/2016

Non-Backtracking Spectrum of Degree-Corrected Stochastic Block Models

Motivated by community detection, we characterise the spectrum of the no...

0 Lennart Gulikers, et al. ∙

research

∙ 11/02/2015

An Impossibility Result for Reconstruction in a Degree-Corrected Planted-Partition Model

We consider a Degree-Corrected Planted-Partition model: a random graph o...

0 Lennart Gulikers, et al. ∙

research

∙ 06/29/2015

A spectral method for community detection in moderately-sparse degree-corrected stochastic block models

We consider community detection in Degree-Corrected Stochastic Block Mod...

0 Lennart Gulikers, et al. ∙

research

∙ 02/16/2015

Clustering and Inference From Pairwise Comparisons

Given a set of pairwise comparisons, the classical ranking problem compu...

0 Rui Wu, et al. ∙

research

∙ 02/11/2015

Reconstruction in the Labeled Stochastic Block Model

The labeled stochastic block model is a random graph model representing ...

0 Marc Lelarge, et al. ∙

research

∙ 06/26/2014

Edge Label Inference in Generalized Stochastic Block Models: from Spectral Theory to Impossibility Results

The classical setting of community detection consists of networks exhibi...

0 Jiaming Xu, et al. ∙

research

∙ 06/18/2012

Comparison-Based Learning with Rank Nets

We consider the problem of search through comparisons, where a user is p...

0 Amin Karbasi, et al. ∙

research

∙ 07/15/2011

From Small-World Networks to Comparison-Based Search

The problem of content search through comparisons has recently received ...

0 Amin Karbasi, et al. ∙

Laurent Massoulie

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