
Correlation detection in trees for partial graph alignment
We consider alignment of sparse graphs, which consists in finding a mapp...
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A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip
We introduce the continuized Nesterov acceleration, a close variant of N...
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Decentralized Optimization with Heterogeneous Delays: a ContinuousTime Approach
In decentralized optimization, nodes of a communication network privatel...
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Concentration of NonIsotropic Random Tensors with Applications to Learning and Empirical Risk Minimization
Dimension is an inherent bottleneck to some modern learning tasks, where...
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Impossibility of Partial Recovery in the Graph Alignment Problem
Random graph alignment refers to recovering the underlying vertex corres...
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Asynchrony and Acceleration in Gossip Algorithms
This paper considers the minimization of a sum of smooth and strongly co...
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Partial Recovery in the Graph Alignment Problem
In this paper, we consider the graph alignment problem, which is the pro...
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DualFree Stochastic Decentralized Optimization with Variance Reduction
We consider the problem of training machine learning models on distribut...
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Understanding and monitoring the local progression of the Covid19 epidemic from medical emergency calls: the example of the Paris area
We portray the evolution of the Covid19 epidemic during the crisis of M...
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Forecasting the local progression of the Covid19 epidemic from medical emergency calls: the example of the Paris area
We portray the evolution of the Covid19 epidemic during the crisis of M...
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An Optimal Algorithm for Decentralized Finite Sum Optimization
Modern largescale finitesum optimization relies on two key aspects: di...
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Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization
We consider the setting of distributed empirical risk minimization where...
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From tree matching to sparse graph alignment
In this paper we consider alignment of sparse graphs, for which we intro...
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An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums
Modern largescale finitesum optimization relies on two key aspects: di...
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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...
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Robustness of spectral methods for community detection
The present work is concerned with community detection. Specifically, we...
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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...
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Efficient inference in stochastic block models with vertex labels
We study the stochastic block model with two communities where vertices ...
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Adaptive Matching for Expert Systems with Uncertain Task Types
Online twosided matching markets such as Q&A forums (e.g. StackOverflow...
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Optimal algorithms for smooth and strongly convex distributed optimization in networks
In this paper, we determine the optimal convergence rates for strongly c...
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NonBacktracking Spectrum of DegreeCorrected Stochastic Block Models
Motivated by community detection, we characterise the spectrum of the no...
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An Impossibility Result for Reconstruction in a DegreeCorrected PlantedPartition Model
We consider a DegreeCorrected PlantedPartition model: a random graph o...
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A spectral method for community detection in moderatelysparse degreecorrected stochastic block models
We consider community detection in DegreeCorrected Stochastic Block Mod...
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Clustering and Inference From Pairwise Comparisons
Given a set of pairwise comparisons, the classical ranking problem compu...
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Reconstruction in the Labeled Stochastic Block Model
The labeled stochastic block model is a random graph model representing ...
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Edge Label Inference in Generalized Stochastic Block Models: from Spectral Theory to Impossibility Results
The classical setting of community detection consists of networks exhibi...
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ComparisonBased Learning with Rank Nets
We consider the problem of search through comparisons, where a user is p...
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From SmallWorld Networks to ComparisonBased Search
The problem of content search through comparisons has recently received ...
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Laurent Massoulie
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