Alexandre d'Aspremont

According to our database1, Alexandre d'Aspremont authored at least 72 papers between 2003 and 2022.

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Bibliography

2022
Convergence of a Constrained Vector Extrapolation Scheme.
SIAM J. Math. Data Sci., 2022

Approximation Bounds for Sparse Programs.
SIAM J. Math. Data Sci., 2022

Optimal complexity and certification of Bregman first-order methods.
Math. Program., 2022

Restarting Frank-Wolfe: Faster Rates under Hölderian Error Bounds.
J. Optim. Theory Appl., 2022

2021
FANOK: Knockoffs in Linear Time.
SIAM J. Math. Data Sci., 2021

Quartic First-Order Methods for Low-Rank Minimization.
J. Optim. Theory Appl., 2021

Ranking and synchronization from pairwise measurements via SVD.
J. Mach. Learn. Res., 2021

Linear Bandits on Uniformly Convex Sets.
J. Mach. Learn. Res., 2021

Acceleration Methods.
Found. Trends Optim., 2021

Local and Global Uniform Convexity Conditions.
CoRR, 2021

A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention.
Proceedings of the 9th International Conference on Learning Representations, 2021

Projection-Free Optimization on Uniformly Convex Sets.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Sharpness, Restart, and Acceleration.
SIAM J. Optim., 2020

Regularized nonlinear acceleration.
Math. Program., 2020

A Bregman Method for Structure Learning on Sparse Directed Acyclic Graphs.
CoRR, 2020

Convergence of Constrained Anderson Acceleration.
CoRR, 2020

Averaging Atmospheric Gas Concentration Data using Wasserstein Barycenters.
CoRR, 2020

An Optimal Transport Kernel for Feature Aggregation and its Relationship to Attention.
CoRR, 2020

Global Convergence of Frank Wolfe on One Hidden Layer Networks.
CoRR, 2020

Complexity Guarantees for Polyak Steps with Momentum.
Proceedings of the Conference on Learning Theory, 2020

Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal Transport.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Screening Data Points in Empirical Risk Minimization via Ellipsoidal Regions and Safe Loss Functions.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Naive Feature Selection: Sparsity in Naive Bayes.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Screening Data Points in Empirical Risk Minimization via Ellipsoidal Regions and Safe Loss Function.
CoRR, 2019

Overcomplete Independent Component Analysis via SDP.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Restarting Frank-Wolfe.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Nonlinear Acceleration of Primal-Dual Algorithms.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Optimal Affine-Invariant Smooth Minimization Algorithms.
SIAM J. Optim., 2018

Reconstructing Latent Orderings by Spectral Clustering.
CoRR, 2018

Nonlinear Acceleration of Deep Neural Networks.
CoRR, 2018

Frank-Wolfe with Subsampling Oracle.
Proceedings of the 35th International Conference on Machine Learning, 2018

Nonlinear Acceleration of CNNs.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
A spectral algorithm for fast de novo layout of uncorrected long nanopore reads.
Bioinform., 2017

Integration Methods and Optimization Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Nonlinear Acceleration of Stochastic Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Phase retrieval for imaging problems.
Math. Program. Comput., 2016

Spectral Ranking using Seriation.
J. Mach. Learn. Res., 2016

2015
Convex Relaxations for Permutation Problems.
SIAM J. Matrix Anal. Appl., 2015

Phase recovery, MaxCut and complex semidefinite programming.
Math. Program., 2015

Supervised Clustering in the Data Cube.
CoRR, 2015

2014
A Stochastic Smoothing Algorithm for Semidefinite Programming.
SIAM J. Optim., 2014

Approximation bounds for sparse principal component analysis.
Math. Program., 2014

On Learning Matrices with Orthogonal Columns or Disjoint Supports.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

SerialRank: Spectral Ranking using Seriation.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Weak Recovery Conditions from Graph Partitioning Bounds and Order Statistics.
Math. Oper. Res., 2013

Mean Reversion with a Variance Threshold.
Proceedings of the 30th International Conference on Machine Learning, 2013

2011
Testing the nullspace property using semidefinite programming.
Math. Program., 2011

Preface.
Math. Program., 2011

2010
Convex Relaxations for Subset Selection
CoRR, 2010

2009
Support vector machine classification with indefinite kernels.
Math. Program. Comput., 2009

White Functionals for Anomaly Detection in Dynamical Systems.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2008
First-Order Methods for Sparse Covariance Selection.
SIAM J. Matrix Anal. Appl., 2008

Smooth Optimization with Approximate Gradient.
SIAM J. Optim., 2008

Optimal Solutions for Sparse Principal Component Analysis.
J. Mach. Learn. Res., 2008

Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data.
J. Mach. Learn. Res., 2008

A Cutting Plane Method for Multiple Kernel Learning
CoRR, 2008

2007
A Direct Formulation for Sparse PCA Using Semidefinite Programming.
SIAM Rev., 2007

Identifying Small Mean Reverting Portfolios
CoRR, 2007

Model Selection Through Sparse Maximum Likelihood Estimation
CoRR, 2007

Clustering and Feature Selection using Sparse Principal Component Analysis
CoRR, 2007

A Semidefinite Relaxation for Air Traffic Flow Scheduling.
Proceedings of the 2007 IEEE International Conference on Research, 2007

Full regularization path for sparse principal component analysis.
Proceedings of the Machine Learning, 2007

2006
Static arbitrage bounds on basket option prices.
Math. Program., 2006

Optimal path planning for air traffic flow management under stochastic weather and capacity constraints.
Proceedings of the 4th International Confernce on Computer Sciences: Research, 2006

Reallocation time calculation according to slot occupation rate.
Proceedings of the 4th International Confernce on Computer Sciences: Research, 2006

Convex optimization techniques for fitting sparse Gaussian graphical models.
Proceedings of the Machine Learning, 2006

2005
A Market Test for the Positivity of Arrow-Debreu Prices
CoRR, 2005

Sparse Covariance Selection via Robust Maximum Likelihood Estimation
CoRR, 2005

2004
Static versus Dynamic Arbitrage Bounds on Multivariate Option Prices
CoRR, 2004

2003
Risk-Management Methods for the Libor Market Model Using Semidefinite Programming
CoRR, 2003

Interest Rate Model Calibration Using Semidefinite Programming
CoRR, 2003

A semidefinite representation for some minimum cardinality problems.
Proceedings of the 42nd IEEE Conference on Decision and Control, 2003


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