Robust algorithms for learning from modern data

Project Information

SEQUOIA

Grant agreement ID: 724063

DOI 10.3030/724063

Project closed

EC signature date 16 March 2017

Start date 1 September 2017

End date 31 August 2023

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost € 1 998 750,00

EU contribution € 1 998 750,00

Coordinated by

INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUE
France

Publications

Peer reviewed articles (6)

Worst-Case Convergence Analysis of Inexact Gradient and Newton Methods Through Semidefinite Programming Performance Estimation

Author(s): Etienne de Klerk; François Glineur; Adrien B. Taylor
Published in: SIAM Journal on Optimization, Issue 21, 2020, ISSN 1052-6234
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/19m1281368

On the oracle complexity of smooth strongly convex minimization

Author(s): Y. Drori; Adrien B. Taylor
Published in: Journal of Complexity, Issue 35, 2021, ISSN 1076-2787
Publisher: John Wiley & Sons Inc.
DOI: 10.1016/j.jco.2021.101590

On the Effectiveness of Richardson Extrapolation in Data Science.

Author(s): F. Bach.
Published in: SIAM Journal on Mathematics of Data Science, 2021, ISSN 2577-0187
Publisher: SIAM
DOI: 10.1137/21m1397349

A note on approximate accelerated forward-backward methods with absolute and relative errors, and possibly strongly convex objectives

Author(s): Mathieu Barré, Adrien Taylor & Francis Bach
Published in: Open Journal of Mathematical Optimization, 2022, ISSN 2777-5860
Publisher: Mersenne
DOI: 10.5802/ojmo.12

Accelerated Gossip in Networks of Given Dimension using Jacobi Polynomial Iterations

Author(s): Raphaël Berthier; Francis Bach; Pierre Gaillard
Published in: SIAM Journal on the Mathematics of Data Science, Issue 13, 2020, ISSN 2577-0187
Publisher: SIAM
DOI: 10.1137/19m1244822

Efficient first-order methods for convex minimization: a constructive approach

Author(s): Yoel Drori, Adrien B. Taylor
Published in: Mathematical Programming, 2018, ISSN 0025-5610
Publisher: Springer Verlag
DOI: 10.1007/s10107-019-01410-2

Conference proceedings (21)

Explicit Regularization of Stochastic Gradient Methods through Duality.

Author(s): A. Raj, F. Bach.
Published in: Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Publisher: AISTATS

A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation.

Author(s): A. Vacher, B. Muzellec, A. Rudi, F. Bach, F.-X. Vialard.
Published in: Proceedings of the Conference on Learning Theory (COLT), 2021, 2021
Publisher: COLT

Dual-Free Stochastic Decentralized Optimization with Variance Reduction.

Author(s): H. Hendrikx, F. Bach, L. Massoulié.
Published in: Advances in Neural Information Processing Systems (NeurIPS), 2020
Publisher: NeurIPS

Non-parametric Models for Non-negative Functions.

Author(s): U. Marteau-Ferey, F. Bach, A. Rudi.
Published in: Advances in Neural Information Processing Systems (NeurIPS)., 2020
Publisher: NeurIPS

Batch Normalization Provably Avoids Rank Collapse for Randomly Initialised Deep Networks.

Author(s): H. Daneshmand, J. Kohler, F. Bach, T. Hofmann, A. Lucchi.
Published in: Advances in Neural Information Processing Systems (NeurIPS), 2020, 2020
Publisher: NeurIPS

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

Author(s): M. Even, R. Berthier, F. Bach, N. Flammarion, P. Gaillard, H. Hendrikx, L. Massoulié, A. Taylor.
Published in: Advances in Neural Information Processing Systems, 2021
Publisher: NeurIPS

Learning with Differentiable Perturbed Optimizers

Author(s): Berthet, Quentin; Blondel, Mathieu; Teboul, Olivier; Cuturi, Marco; Vert, Jean-Philippe; Bach, Francis
Published in: Advances in NeurIPS, Issue 39, 2020
Publisher: NeurIPS

Relating Leverage Scores and Density using Regularized Christoffel Functions

Author(s): Pauwels , Edouard; Bach , Francis; Vert , Jean-Philippe
Published in: Advances in NIPS, 2018
Publisher: NIPS Foundation

Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes

Author(s): Loucas Pillaud-Vivien, Alessandro Rudi, Francis Bach
Published in: Advances in Neural Information Processing Systems (NIPS), 2018
Publisher: NIPS Foundation

On Fast Leverage Score Sampling and Optimal Learning

Author(s): Rudi , Alessandro; Calandriello , Daniele; Carratino , Luigi; Rosasco , Lorenzo
Published in: Advances in NIPS, Issue 28, 2018
Publisher: NIPS Foundation

Exponential convergence of testing error for stochastic gradient methods

Author(s): Pillaud-Vivien, Loucas; Rudi, Alessandro; Bach, Francis
Published in: Proceedings of COLT, Issue 5, 2018
Publisher: COLT

On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport

Author(s): Chizat , Lenaic; Bach , Francis
Published in: Advances in NIPS, Issue 1, 2018
Publisher: NIPS Foundation

Stochastic first-order methods: non-asymptotic and computer-aided analyses via potential functions

Author(s): Adrien Taylor, Francis Bach
Published in: Proceedings COLT, 2019
Publisher: COLT

Affine Invariant Covariance Estimation for Heavy-Tailed Distributions

Author(s): Ostrovskii, Dmitrii; Rudi, Alessandro
Published in: COLT 2019 - 32nd Annual Conference on Learning Theory, Issue 5, 2019
Publisher: N/A

An accelerated decentralized stochastic proximal algorithm for finite Sums

Author(s): Hadrien Hendrikx, Francis Bach, Laurent Massoulié
Published in: Advances in Neural Information Processing Systems (NeurIPS), 2019
Publisher: N/A

On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport

Author(s): Chizat , Lenaic; Bach , Francis
Published in: Advances in Neural Information Processing Systems (NIPS), Issue 2, 2018
Publisher: N/A

Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses

Author(s): Marteau-Ferey, Ulysse; Bach, Francis; Rudi, Alessandro
Published in: Advances in Neural Information Processing Systems (NeurIPS), 2019
Publisher: N/A

On Lazy Training in Differentiable Programming

Author(s): Chizat, Lenaic; Oyallon, Edouard; Bach, Francis
Published in: NeurIPS 2019 - 33rd Conference on Neural Information Processing Systems, Dec 2019, Vancouver, Canada, Issue 15, 2019
Publisher: N/A

Deep Equals Shallow for ReLU Networks in Kernel Regimes.

Author(s): A. Bietti, F. Bach.
Published in: Proceedings of the International Conference on Learning Representations (ICLR), 2021
Publisher: ICLR

Batch Normalization Orthogonalizes Representations in Deep Random Networks

Author(s): H. Daneshmand, A. Joudaki, F. Bach.
Published in: Advances in NeurIPS, 2021
Publisher: NeurIPS

Fast rates in structured prediction.

Author(s): V. Cabannes, F. Bach, A. Rudi.
Published in: Proceedings of the Conference on Learning Theory (COLT), 2021
Publisher: COLT

Non-peer reviewed articles (1)

Finite-sample analysis of M-estimators using self-concordance

Author(s): Dmitrii Ostrovskii; Francis Bach
Published in: Electronic Journal of Statistics, Issue 27, 2021, ISSN 1935-7524
Publisher: Institute of Mathematical Statistics
DOI: 10.1214/20-ejs1780