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2020 – today
- 2024
[j17]Baptiste Goujaud, Céline Moucer, François Glineur, Julien M. Hendrickx, Adrien B. Taylor, Aymeric Dieuleveut:
PEPit: computer-assisted worst-case analyses of first-order optimization methods in Python. Math. Program. Comput. 16(3): 337-367 (2024)- [c12]Antoine Bambade, Fabian Schramm, Adrien B. Taylor, Justin Carpentier:
Leveraging augmented-Lagrangian techniques for differentiating over infeasible quadratic programs in machine learning. ICLR 2024 - 2023
- [j16]Baptiste Goujaud
, Aymeric Dieuleveut, Adrien B. Taylor:
Counter-Examples in First-Order Optimization: A Constructive Approach. IEEE Control. Syst. Lett. 7: 2485-2490 (2023) - [j15]Adrien B. Taylor, Yoel Drori:
An optimal gradient method for smooth strongly convex minimization. Math. Program. 199(1): 557-594 (2023) - [j14]Mathieu Barré, Adrien B. Taylor, Francis R. Bach:
Principled analyses and design of first-order methods with inexact proximal operators. Math. Program. 201(1): 185-230 (2023) - [j13]Céline Moucer, Adrien B. Taylor, Francis R. Bach:
A Systematic Approach to Lyapunov Analyses of Continuous-Time Models in Convex Optimization. SIAM J. Optim. 33(3): 1558-1586 (2023) - [c11]Baptiste Goujaud, Aymeric Dieuleveut, Adrien B. Taylor:
On Fundamental Proof Structures in First-Order Optimization. CDC 2023: 3023-3030 - [c10]Eduard Gorbunov, Adrien B. Taylor, Samuel Horváth, Gauthier Gidel:
Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicity. ICML 2023: 11614-11641 - 2022
- [j12]Yoel Drori, Adrien B. Taylor:
On the oracle complexity of smooth strongly convex minimization. J. Complex. 68: 101590 (2022) - [j11]Radu-Alexandru Dragomir, Adrien B. Taylor, Alexandre d'Aspremont, Jérôme Bolte:
Optimal complexity and certification of Bregman first-order methods. Math. Program. 194(1): 41-83 (2022) - [j10]Mathieu Barré, Adrien B. Taylor, Francis R. Bach:
A note on approximate accelerated forward-backward methods with absolute and relative errors, and possibly strongly convex objectives. Open J. Math. Optim. 3: 1-15 (2022) - [j9]Mathieu Barré, Adrien B. Taylor, Alexandre d'Aspremont:
Convergence of a Constrained Vector Extrapolation Scheme. SIAM J. Math. Data Sci. 4(3): 979-1002 (2022) - [c9]Baptiste Goujaud, Damien Scieur, Aymeric Dieuleveut, Adrien B. Taylor, Fabian Pedregosa:
Super-Acceleration with Cyclical Step-sizes. AISTATS 2022: 3028-3065 - [c8]Benjamin Dubois-Taine, Francis R. Bach, Quentin Berthet, Adrien B. Taylor:
Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization. NeurIPS 2022 - [c7]Eduard Gorbunov, Adrien B. Taylor, Gauthier Gidel:
Last-Iterate Convergence of Optimistic Gradient Method for Monotone Variational Inequalities. NeurIPS 2022 - [c6]Antoine Bambade, Sarah El Kazdadi, Adrien B. Taylor, Justin Carpentier:
PROX-QP: Yet another Quadratic Programming Solver for Robotics and beyond. Robotics: Science and Systems 2022 - [i12]Baptiste Goujaud, Céline Moucer, François Glineur, Julien M. Hendrickx, Adrien B. Taylor, Aymeric Dieuleveut:
PEPit: computer-assisted worst-case analyses of first-order optimization methods in Python. CoRR abs/2201.04040 (2022) - [i11]Benjamin Dubois-Taine, Francis R. Bach, Quentin Berthet, Adrien B. Taylor:
Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization. CoRR abs/2205.12751 (2022) - [i10]Céline Moucer, Adrien B. Taylor, Francis R. Bach:
A systematic approach to Lyapunov analyses of continuous-time models in convex optimization. CoRR abs/2205.12772 (2022) - 2021
- [j8]Alexandre d'Aspremont, Damien Scieur, Adrien B. Taylor:
Acceleration Methods. Found. Trends Optim. 5(1-2): 1-245 (2021) - [c5]Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Hadrien Hendrikx, Pierre Gaillard, Laurent Massoulié, Adrien B. Taylor:
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms. NeurIPS 2021: 28054-28066 - [i9]Alexandre d'Aspremont, Damien Scieur, Adrien B. Taylor:
Acceleration Methods. CoRR abs/2101.09545 (2021) - [i8]Adrien B. Taylor, Yoel Drori:
An optimal gradient method for smooth (possibly strongly) convex minimization. CoRR abs/2101.09741 (2021) - [i7]Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Pierre Gaillard, Adrien B. Taylor:
A Continuized View on Nesterov Acceleration. CoRR abs/2102.06035 (2021) - [i6]Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Pierre Gaillard, Hadrien Hendrikx, Laurent Massoulié, Adrien B. Taylor:
A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip. CoRR abs/2106.07644 (2021) - 2020
- [j7]Yoel Drori, Adrien B. Taylor:
Efficient first-order methods for convex minimization: a constructive approach. Math. Program. 184(1): 183-220 (2020) - [j6]Etienne de Klerk, François Glineur, Adrien B. Taylor:
Worst-Case Convergence Analysis of Inexact Gradient and Newton Methods Through Semidefinite Programming Performance Estimation. SIAM J. Optim. 30(3): 2053-2082 (2020) - [j5]Ernest K. Ryu, Adrien B. Taylor, Carolina Bergeling, Pontus Giselsson:
Operator Splitting Performance Estimation: Tight Contraction Factors and Optimal Parameter Selection. SIAM J. Optim. 30(3): 2251-2271 (2020) - [c4]Mathieu Barré, Adrien B. Taylor, Alexandre d'Aspremont:
Complexity Guarantees for Polyak Steps with Momentum. COLT 2020: 452-478 - [i5]Mathieu Barré, Adrien B. Taylor, Alexandre d'Aspremont:
Complexity Guarantees for Polyak Steps with Momentum. CoRR abs/2002.00915 (2020) - [i4]Mathieu Barré, Adrien B. Taylor, Francis R. Bach:
Principled Analyses and Design of First-Order Methods with Inexact Proximal Operators. CoRR abs/2006.06041 (2020) - [i3]Mathieu Barré, Adrien B. Taylor, Alexandre d'Aspremont:
Convergence of Constrained Anderson Acceleration. CoRR abs/2010.15482 (2020)
2010 – 2019
- 2019
- [c3]Adrien B. Taylor, Francis R. Bach:
Stochastic first-order methods: non-asymptotic and computer-aided analyses via potential functions. COLT 2019: 2934-2992 - [i2]Adrien B. Taylor, Francis R. Bach:
Stochastic first-order methods: non-asymptotic and computer-aided analyses via potential functions. CoRR abs/1902.00947 (2019) - [i1]Radu-Alexandru Dragomir, Adrien B. Taylor, Alexandre d'Aspremont, Jérôme Bolte:
Optimal Complexity and Certification of Bregman First-Order Methods. CoRR abs/1911.08510 (2019) - 2018
- [j4]Adrien B. Taylor, Julien M. Hendrickx, François Glineur:
Exact Worst-Case Convergence Rates of the Proximal Gradient Method for Composite Convex Minimization. J. Optim. Theory Appl. 178(2): 455-476 (2018) - [c2]Adrien B. Taylor, Bryan Van Scoy, Laurent Lessard:
Lyapunov Functions for First-Order Methods: Tight Automated Convergence Guarantees. ICML 2018: 4904-4913 - 2017
- [b1]Adrien B. Taylor:
Convex interpolation and performance estimation of first-order methods for convex optimization. Catholic University of Louvain, Louvain-la-Neuve, Belgium, 2017 - [j3]Adrien B. Taylor, Julien M. Hendrickx, François Glineur:
Smooth strongly convex interpolation and exact worst-case performance of first-order methods. Math. Program. 161(1-2): 307-345 (2017) - [j2]Etienne de Klerk, François Glineur, Adrien B. Taylor:
On the worst-case complexity of the gradient method with exact line search for smooth strongly convex functions. Optim. Lett. 11(7): 1185-1199 (2017) - [j1]Adrien B. Taylor, Julien M. Hendrickx, François Glineur:
Exact Worst-Case Performance of First-Order Methods for Composite Convex Optimization. SIAM J. Optim. 27(3): 1283-1313 (2017) - [c1]Adrien B. Taylor, Julien M. Hendrickx, François Glineur:
Performance estimation toolbox (PESTO): Automated worst-case analysis of first-order optimization methods. CDC 2017: 1278-1283
Coauthor Index
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