Loucas Pillaud-Vivien

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All published works

Action	Title	Year	Authors
+ PDF Chat	Stochastic Differential Equations models for Least-Squares Stochastic Gradient Descent	2024	Adrien Schertzer Loucas Pillaud-Vivien
+ PDF Chat	An Ordering of Divergences for Variational Inference with Factorized Gaussian Approximations	2024	Charles C. Margossian Loucas Pillaud-Vivien Lawrence K. Saul
+ PDF Chat	The Computational Complexity of Learning Gaussian Single-Index Models	2024	Alex Damian Loucas Pillaud-Vivien Jason D. Lee Joan Bruna
+ PDF Chat	Batch and match: black-box variational inference with a score-based divergence	2024	Diana Cai Chirag Modi Loucas Pillaud-Vivien Charles C. Margossian Robert M. Gower David M. Blei Lawrence K. Saul
+	Kernelized Diffusion maps	2023	Loucas Pillaud-Vivien Francis Bach
+	On Single Index Models beyond Gaussian Data	2023	Joan Bruna Loucas Pillaud-Vivien Aaron Zweig
+	On Learning Gaussian Multi-index Models with Gradient Flow	2023	Alberto Bietti Joan Bruna Loucas Pillaud-Vivien
+ PDF Chat	Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs	2022	Etienne Boursier Loucas Pillaud-Vivien Nicolas Flammarion
+ PDF Chat	Label noise (stochastic) gradient descent implicitly solves the Lasso for quadratic parametrisation	2022	Loucas Pillaud-Vivien Julien Reygner Nicolas Flammarion
+	Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs	2022	Etienne Boursier Loucas Pillaud-Vivien Nicolas Flammarion
+	SGD with Large Step Sizes Learns Sparse Features	2022	Maksym Andriushchenko Aditya Varre Loucas Pillaud-Vivien Nicolas Flammarion
+	Label noise (stochastic) gradient descent implicitly solves the Lasso for quadratic parametrisation	2022	Loucas Pillaud-Vivien Julien Reygner Nicolas Flammarion
+ PDF Chat	Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning	2021	Vivien Cabannes Loucas Pillaud-Vivien Francis Bach Alessandro Rudi
+	Last iterate convergence of SGD for Least-Squares in the Interpolation regime	2021	Aditya Varre Loucas Pillaud-Vivien Nicolas Flammarion
+	Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity	2021	Scott Pesme Loucas Pillaud-Vivien Nicolas Flammarion
+	Last iterate convergence of SGD for Least-Squares in the Interpolation regime	2021	Aditya Varre Loucas Pillaud-Vivien Nicolas Flammarion
+	Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity	2021	Scott Pesme Loucas Pillaud-Vivien Nicolas Flammarion
+ PDF Chat	Learning with reproducing kernel Hilbert spaces : stochastic gradient descent and laplacian estimation	2020	Loucas Pillaud-Vivien
+	Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning	2020	Vivien Cabannes Loucas Pillaud-Vivien Francis Bach Alessandro Rudi
+	Statistical Estimation of the Poincar{é} constant and Application to Sampling Multimodal Distributions	2019	Loucas Pillaud-Vivien Francis Bach Tony Lelièvre Alessandro Rudi Gabriel Stoltz
+ PDF Chat	Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes	2018	Loucas Pillaud-Vivien Alessandro Rudi Francis Bach
+	Central Limit Theorem for stationary Fleming-Viot particle systems in finite spaces	2018	Tony Lelièvre Loucas Pillaud-Vivien Julien Reygner
+	Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes	2018	Loucas Pillaud-Vivien Alessandro Rudi Francis Bach
+	Exponential convergence of testing error for stochastic gradient methods	2017	Loucas Pillaud-Vivien Alessandro Rudi Francis Bach

Common Coauthors

Coauthor	Papers Together
Nicolas Flammarion	9
Alessandro Rudi	6
Francis Bach	5
Joan Bruna	3
Aditya Varre	3
Julien Reygner	3
Francis Bach	2
Tony Lelièvre	2
Vivien Cabannes	2
Etienne Boursier	2
Scott Pesme	2
Lawrence K. Saul	2
Charles C. Margossian	2
Gabriel Stoltz	1
Adrien Schertzer	1
Robert M. Gower	1
David M. Blei	1
Aaron Zweig	1
Alberto Bietti	1
Alex Damian	1
Maksym Andriushchenko	1
Diana Cai	1
Chirag Modi	1
Jason D. Lee	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Optimal rates for spectral algorithms with least-squares regression over Hilbert spaces	2018	Junhong Lin Alessandro Rudi Lorenzo Rosasco Volkan Cevher	2
+	A Consistent Regularization Approach for Structured Prediction	2016	Carlo Ciliberto Alessandro Rudi Lorenzo Rosasco	2
+ PDF Chat	On some extensions of Bernstein’s inequality for self-adjoint operators	2017	Stanislav Minsker	2
+ PDF Chat	Optimal Rates for the Regularized Least-Squares Algorithm	2006	Andrea Caponnetto Ernesto De Vito	2
+	On Structured Prediction Theory with Calibrated Convex Surrogate Losses	2017	Anton Osokin Francis Bach Simon Lacoste-Julien	2
+	FALKON: An Optimal Large Scale Kernel Method	2017	Alessandro Rudi Luigi Carratino Lorenzo Rosasco	2
+	SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives	2014	Aaron Defazio Francis Bach Simon Lacoste-Julien	2
+	Generalization Properties of Learning with Random Features	2017	Alessandro Rudi Lorenzo Rosasco	2
+	A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Training Sets	2012	Nicolas Le Roux Mark Schmidt Francis Bach	2
+	Fast Convergence of Stochastic Gradient Descent under a Strong Growth Condition	2013	Mark Schmidt Nicolas Le Roux	2
+	On Early Stopping in Gradient Descent Learning	2007	Yuan Yao Lorenzo Rosasco Andrea Caponnetto	2
+	On the Control of an Interacting Particle Estimation of Schrödinger Ground States	2006	Mathias Rousset	1
+	An idea on proving weighted Sobolev embeddings	2010	Klaus Gansberger	1
+ PDF Chat	Tagged Particle Limit for a Fleming-Viot Type System	2006	Ilie Grigorescu Min Ho Kang	1
+	Derivative reproducing properties for kernel methods in learning theory	2007	Ding‐Xuan Zhou	1
+	Robust Stochastic Approximation Approach to Stochastic Programming	2009	Arkadi Nemirovski Anatoli Juditsky Guanghui Lan Alexander Shapiro	1
+	Topics in propagation of chaos	1991	Alain‐Sol Sznitman	1
+	Quantitative results for the Fleming–Viot particle system and quasi-stationary distributions in discrete space	2015	Bertrand Cloez Marie-Noémie Thai	1
+	Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n)	2013	Francis Bach Éric Moulines	1
+	A general two-scale criteria for logarithmic Sobolev inequalities	2008	Tony Lelièvre	1
+	Hydrodynamic limit for a Fleming–Viot type system	2003	Ilie Grigorescu Min Ho Kang	1
+	On an Infinite-Dimensional Version of S. N. Bernstein’s Inequalities	1970	V. V. Yurinskii	1
+	A stationary Fleming–Viot type Brownian particle system	2008	Jörg‐Uwe Löbus	1
+ PDF Chat	The Geometry of Algorithms with Orthogonality Constraints	1998	Alan Edelman T. A. Arias Steven T. Smith	1
+	Smooth discrimination analysis	1999	Enno Mammen Alexandre B. Tsybakov	1
+ PDF Chat	Isoperimetric problems for convex bodies and a localization lemma	1995	Ravi Kannan László Lovász Miklós Simonovits	1
+ PDF Chat	Quasistationary Distributions and Fleming-Viot Processes in Finite Spaces	2011	Amine Asselah Pablo A. Ferrari Pablo Groisman	1
+	A new criterion for the logarithmic Sobolev inequality and two applications	2006	Félix Otto Maria G. Reznikoff	1
+	On the exponential value of labeled samples	1995	Vittorio Castelli Thomas M. Cover	1
+	Online Learning as Stochastic Approximation of Regularization Paths: Optimality and Almost-Sure Convergence	2014	Pierre Tarrès Yuan Yao	1
+ PDF Chat	A Note on an Inequality Involving the Normal Distribution	1981	Herman Chernoff	1
+ PDF Chat	Sur quelques algorithmes récursifs pour les probabilités numériques	2001	Gilles Pagès	1
+ PDF Chat	Accelerated dynamics: Mathematical foundations and algorithmic improvements	2015	Tony Lelièvre	1
+	Graph Laplacians and their Convergence on Random Neighborhood Graphs	2007	Matthias Hein Jean-Yves Audibert Ulrike von Luxburg	1
+	Optimum Bounds for the Distributions of Martingales in Banach Spaces	1994	Iosif Pinelis	1
+ PDF Chat	Particle approximations of Lyapunov exponents connected to Schrödinger operators and Feynman–Kac semigroups	2003	Pierre Del Moral Laurent Miclo	1
+	Markov Chain Monte Carlo in Practice	1995	Walter R. Gilks Sylvia Richardson David J. Spiegelhalter	1
+	Spline Models for Observational Data.	1991	Hans‐Georg Müller Grace Wahba	1
+	Minimax nonparametric classification .I. Rates of convergence	1999	Yuhong Yang	1
+	Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data	2009	Boaz Nadler Nathan Srebro Xueyuan Zhou	1
+ PDF Chat	Bounds on the Lambert Function and Their Application to the Outage Analysis of User Cooperation	2013	Ioannis Chatzigeorgiou	1
+ PDF Chat	Dimensionality Reduction for Supervised Learning With Reproducing Kernel Hilbert Spaces	2003	Kenji Fukumizu Francis R. Bach Michael I. Jordan	1
+ PDF Chat	Free energy methods for Bayesian inference: efficient exploration of univariate Gaussian mixture posteriors	2011	Nicolás Chopin Tony Lelièvre Gabriel Stoltz	1
+	Bayesian Learning via Stochastic Gradient Langevin Dynamics	2011	Max Welling Yee Whye Teh	1
+	Manopt, a Matlab toolbox for optimization on manifolds	2013	Nicolas Boumal Bamdev Mishra Pierre-Antoine Absil Rodolphe Sepulchre	1
+	Generalization error bounds in semi-supervised classification under the cluster assumption	2006	Philippe Rigollet	1
+	On quasi-stationary distributions in absorbing continuous-time finite Markov chains	1967	J. N. Darroch E. Seneta	1
+	A Fleming–Viot Particle Representation¶of the Dirichlet Laplacian	2000	Krzysztof Burdzy Robert Hołyst Peter March	1
+	Optimal Rates for Regularized Least Squares Regression.	2009	Ingo Steinwart Don Hush Clint Scovel	1
+ PDF Chat	Quasi Stationary Distributions and Fleming-Viot Processes in Countable Spaces	2007	Pablo A. Ferrari Nevena Marić	1