
MetFlow: A New Efficient Method for Bridging the Gap between Markov Chain Monte Carlo and Variational Inference
In this contribution, we propose a new computationally efficient method ...
read it

On LastLayer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation
Uncertainty quantification for deep learning is a challenging open probl...
read it

Highdimensional Bayesian inference via the Unadjusted Langevin Algorithm
We consider in this paper the problem of sampling a highdimensional pro...
read it

On the Online FrankWolfe Algorithms for Convex and Nonconvex Optimizations
In this paper, the online variants of the classical FrankWolfe algorith...
read it

Probabilistic lowrank matrix completion on finite alphabets
The task of reconstructing a matrix given a sample of observedentries is...
read it

Nonstronglyconvex smooth stochastic approximation with convergence rate O(1/n)
We consider the stochastic approximation problem where a convex function...
read it

Testing for Homogeneity with Kernel Fisher Discriminant Analysis
We propose to investigate test statistics for testing homogeneity in rep...
read it

Fixed Rank Kriging for Cellular Coverage Analysis
Coverage planning and optimization is one of the most crucial tasks for ...
read it

MONK  OutlierRobust Mean Embedding Estimation by MedianofMeans
Mean embeddings provide an extremely flexible and powerful tool in machi...
read it

Spatial Prediction Under Location Uncertainty In Cellular Networks
Coverage optimization is an important process for the operator as it is ...
read it

Main effects and interactions in mixed and incomplete data frames
A mixed data frame (MDF) is a table collecting categorical, numerical an...
read it

Density estimation for RWRE
We consider the problem of nonparametric density estimation of a random...
read it

Diffusion approximations and control variates for MCMC
A new methodology is presented for the construction of control variates ...
read it

Analysis of nonsmooth stochastic approximation: the differential inclusion approach
In this paper we address the convergence of stochastic approximation whe...
read it

On stability of a class of filters for nonlinear stochastic systems
This article considers stability properties of a broad class of commonly...
read it

The promises and pitfalls of Stochastic Gradient Langevin Dynamics
Stochastic Gradient Langevin Dynamics (SGLD) has emerged as a key MCMC a...
read it

Lowrank Interaction with Sparse Additive Effects Model for Large Data Frames
Many applications of machine learning involve the analysis of large data...
read it

Nonasymptotic Analysis of Biased Stochastic Approximation Scheme
Stochastic approximation (SA) is a key method used in statistical learni...
read it

On stochastic gradient Langevin dynamics with dependent data streams: the fully nonconvex case
We consider the problem of sampling from a target distribution which is ...
read it

A quantitative Mc Diarmid's inequality for geometrically ergodic Markov chains
We state and prove a quantitative version of the bounded difference ineq...
read it

Unifying mirror descent and dual averaging
We introduce and analyse a new family of algorithms which generalizes an...
read it

On the Global Convergence of (Fast) Incremental Expectation Maximization Methods
The EM algorithm is one of the most popular algorithm for inference in l...
read it

fSAEM: A fast Stochastic Approximation of the EM algorithm for nonlinear mixed effects models
The ability to generate samples of the random effects from their conditi...
read it

Finite Time Analysis of Linear Twotimescale Stochastic Approximation with Markovian Noise
Linear twotimescale stochastic approximation (SA) scheme is an importan...
read it

Convergence Analysis of Riemannian Stochastic Approximation Schemes
This paper analyzes the convergence for a large class of Riemannian stoc...
read it
Eric Moulines
is this you? claim profile