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This work considers gradient descent for L-smooth convex optimization with stepsizes larger than the classic regime where descent can be ensured.
A method for solving the convex programming problem with convergence rate o ( 1 / k 2 ) o(1/k^{2})
Yurii Nesterov · 1983
Earlier work this paper cites.
Problem Complexity and Method Efficiency in Optimization
A. Nemirovski and D. Yudin · 1983
Earlier work this paper cites.
Performance of first-order methods for smooth convex minimization: a novel approach
Yoel Drori and Marc Teboulle · 2012
Earlier work this paper cites.
Smooth strongly convex interpolation and exact worst-case performance of first-order methods
Adrien B. Taylor, Julien M. Hendrickx, and François Glineur · 2015
Earlier work this paper cites.
Smooth strongly convex interpolation and exact worst-case performance of first-order methods
Adrien Taylor, Julien Hendrickx, and François Glineur · 2017
Earlier work this paper cites.
Exact worst-case performance of first-order methods for composite convex optimization
Adrien Taylor, Julien Hendrickx, and François Glineur · 2017
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Greed, hedging, and acceleration in convex optimization
Jason Altschuler · 2018
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Lectures on Convex Optimization
Yurii Nesterov · 2018
Cited alongside, same era.
Performance estimation of the gradient method with fixed arbitrary step sizes
Antoine Daccache · 2019
Cited alongside, same era.
Optimizing the efficiency of first-order methods for decreasing the gradient of smooth convex functions
Donghwan Kim and Jeffrey A. Fessler · 2021
Cited alongside, same era.
An elementary approach to tight worst case complexity analysis of gradient based methods
Marc Teboulle and Yakov Vaisbourd · 2022
Cited alongside, same era.
Worst-case functions for the gradient method with fixed variable step sizes
Diego Eloi · 2022
Cited alongside, same era.
Accelerated gradient descent via long steps, 2023
Benjamin Grimmer, Kevin Shu, and Alex L. Wang · 2023
Cited alongside, same era.
Provably Faster Gradient Descent via Long Steps
B. Grimmer · 2023
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Acceleration by stepsize hedging i: Multi-step descent and the silver stepsize schedule, 2023
Jason M. Altschuler and Pablo A. Parrilo · 2023
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Acceleration by stepsize hedging ii: Silver stepsize schedule for smooth convex optimization, 2023
Jason M. Altschuler and Pablo A. Parrilo · 2023
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Time-reversed dissipation induces duality between minimizing gradient norm and function value, 2023
Jaeyeon Kim, Asuman Ozdaglar, Chanwoo Park, and Ernest K. Ryu · 2023
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Mathematica, Version 13.3
Wolfram Research, Inc · 2023
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On averaging and extrapolation for gradient descent, 2024
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Branch-and-bound performance estimation programming: A unified methodology for constructing optimal optimization methods
Shuvomoy Das Gupta, Bart P.G. Van Parys, and Ernest Ryu · 2023
Cited alongside, same era.
Alan Luner and Benjamin Grimmer · 2024
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