Adrien B. Taylor

According to our database, Adrien B. Taylor authored at least 36 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Automated tight Lyapunov analysis for first-order methods.

Manu Upadhyaya, Sebastian Banert, Adrien B. Taylor, Pontus Giselsson

Math. Program., January, 2025

2024

PEPit: computer-assisted worst-case analyses of first-order optimization methods in Python.

Baptiste Goujaud, Céline Moucer, François Glineur, Julien M. Hendrickx, Adrien B. Taylor, Aymeric Dieuleveut

Math. Program. Comput., September, 2024

Short Paper - Quadratic minimization: from conjugate gradient to an adaptive Polyak's momentum method with Polyak step-sizes.

Baptiste Goujaud, Adrien B. Taylor, Aymeric Dieuleveut

Open J. Math. Optim., 2024

Leveraging augmented-Lagrangian techniques for differentiating over infeasible quadratic programs in machine learning.

Antoine Bambade, Fabian Schramm, Adrien B. Taylor, Justin Carpentier

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

A Systematic Approach to Lyapunov Analyses of Continuous-Time Models in Convex Optimization.

Céline Moucer, Adrien B. Taylor, Francis R. Bach

SIAM J. Optim., September, 2023

An optimal gradient method for smooth strongly convex minimization.

Adrien B. Taylor, Yoel Drori

Math. Program., May, 2023

Principled analyses and design of first-order methods with inexact proximal operators.

Mathieu Barré, Adrien B. Taylor, Francis R. Bach

Math. Program., 2023

Counter-Examples in First-Order Optimization: A Constructive Approach.

Baptiste Goujaud, Aymeric Dieuleveut, Adrien B. Taylor

IEEE Control. Syst. Lett., 2023

Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicity.

Eduard Gorbunov, Adrien B. Taylor, Samuel Horváth, Gauthier Gidel

Proceedings of the International Conference on Machine Learning, 2023

On Fundamental Proof Structures in First-Order Optimization.

Baptiste Goujaud, Aymeric Dieuleveut, Adrien B. Taylor

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

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

Mathieu Barré, Adrien B. Taylor, Francis R. Bach

Open J. Math. Optim., March, 2022

Convergence of a Constrained Vector Extrapolation Scheme.

Mathieu Barré, Adrien B. Taylor, Alexandre d'Aspremont

SIAM J. Math. Data Sci., 2022

Optimal complexity and certification of Bregman first-order methods.

Radu-Alexandru Dragomir, Adrien B. Taylor, Alexandre d'Aspremont, Jérôme Bolte

Math. Program., 2022

On the oracle complexity of smooth strongly convex minimization.

Yoel Drori, Adrien B. Taylor

J. Complex., 2022

PROX-QP: Yet another Quadratic Programming Solver for Robotics and beyond.

Antoine Bambade, Sarah El Kazdadi, Adrien B. Taylor, Justin Carpentier

Proceedings of the Robotics: Science and Systems XVIII, New York City, NY, USA, June 27, 2022

Last-Iterate Convergence of Optimistic Gradient Method for Monotone Variational Inequalities.

Eduard Gorbunov, Adrien B. Taylor, Gauthier Gidel

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization.

Benjamin Dubois-Taine, Francis R. Bach, Quentin Berthet, Adrien B. Taylor

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Super-Acceleration with Cyclical Step-sizes.

Baptiste Goujaud, Damien Scieur, Aymeric Dieuleveut, Adrien B. Taylor, Fabian Pedregosa

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Acceleration Methods.

Alexandre d'Aspremont, Damien Scieur, Adrien B. Taylor

Found. Trends Optim., 2021

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

Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Pierre Gaillard, Hadrien Hendrikx, Laurent Massoulié, Adrien B. Taylor

CoRR, 2021

A Continuized View on Nesterov Acceleration.

Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Pierre Gaillard, Adrien B. Taylor

CoRR, 2021

An optimal gradient method for smooth (possibly strongly) convex minimization.

Adrien B. Taylor, Yoel Drori

CoRR, 2021

Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms.

Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Hadrien Hendrikx, Pierre Gaillard, Laurent Massoulié, Adrien B. Taylor

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Operator Splitting Performance Estimation: Tight Contraction Factors and Optimal Parameter Selection.

Ernest K. Ryu, Adrien B. Taylor, Carolina Bergeling, Pontus Giselsson

SIAM J. Optim., 2020

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

Etienne de Klerk, François Glineur, Adrien B. Taylor

SIAM J. Optim., 2020

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

Yoel Drori, Adrien B. Taylor

Math. Program., 2020

Convergence of Constrained Anderson Acceleration.

Mathieu Barré, Adrien B. Taylor, Alexandre d'Aspremont

CoRR, 2020

Complexity Guarantees for Polyak Steps with Momentum.

Mathieu Barré, Adrien B. Taylor, Alexandre d'Aspremont

Proceedings of the Conference on Learning Theory, 2020

2019

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

Adrien B. Taylor, Francis R. Bach

Proceedings of the Conference on Learning Theory, 2019

2018

Exact Worst-Case Convergence Rates of the Proximal Gradient Method for Composite Convex Minimization.

Adrien B. Taylor, Julien M. Hendrickx, François Glineur

J. Optim. Theory Appl., 2018

Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees.

Adrien B. Taylor, Bryan Van Scoy, Laurent Lessard

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Convex interpolation and performance estimation of first-order methods for convex optimization.

Adrien B. Taylor

PhD thesis, 2017

Exact Worst-Case Performance of First-Order Methods for Composite Convex Optimization.

Adrien B. Taylor, Julien M. Hendrickx, François Glineur

SIAM J. Optim., 2017

On the worst-case complexity of the gradient method with exact line search for smooth strongly convex functions.

Etienne de Klerk, François Glineur, Adrien B. Taylor

Optim. Lett., 2017

Smooth strongly convex interpolation and exact worst-case performance of first-order methods.

Adrien B. Taylor, Julien M. Hendrickx, François Glineur

Math. Program., 2017

Performance estimation toolbox (PESTO): Automated worst-case analysis of first-order optimization methods.

Adrien B. Taylor, Julien M. Hendrickx, François Glineur

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017