When is Momentum Extragradient Optimal? A Polynomial-Based Analysis
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Abstract (arXiv)
The extragradient method has gained popularity due to its robust convergence properties for differentiable games. Unlike single-objective optimization, game dynamics involve complex interactions reflected by the eigenvalues of the game vector field's Jacobian scattered across the complex plane. This complexity can cause the simple gradient method to diverge, even for bilinear games, while the extragradient method achieves convergence. Building on the recently proven accelerated convergence of the momentum extragradient method for bilinear games citepazizian2020accelerating, we use a polynomial-based analysis to identify three distinct scenarios where this method exhibits further accelerated convergence. These scenarios encompass situations where the eigenvalues reside on the (positive) real line, lie on the real line alongside complex conjugates, or exist solely as complex conjugates. Furthermore, we derive the hyperparameters for each scenario that achieve the fastest convergence rate.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 36 of its 61 references that are in the map. First posted on arXiv 9 Nov 2022.
Builds on
36 of 61 references.
References · 36
- 2020Sharpness-Aware Minimization for Efficiently Improving Generalizationcited by 1,417
- 2018Which Training Methods for GANs do actually Converge?cited by 679
- 2017Training GANs with Optimismcited by 217
- 2018A Variational Inequality Perspective on Generative Adversarial Networkscited by 144
- 2019A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approachcited by 143
- 2017Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Playcited by 141
- 2018The Mechanics of n-Player Differentiable Gamescited by 118
- 2017The Numerics of GANscited by 105
- 2018The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimizationcited by 101
- 2020Traces of Class/Cross-Class Structure Pervade Deep Learning Spectracited by 94
- 2019On the convergence of single-call stochastic extra-gradient methodscited by 89
- 2018Interaction Matters: A Note on Non-asymptotic Local Convergence of Generative Adversarial Networkscited by 68
24 more
- 2016Stochastic Variance Reduction Methods for Saddle-Point Problemscited by 60
- 2018Negative Momentum for Improved Game Dynamicscited by 60
- 2016Connecting Generative Adversarial Networks and Actor-Critic Methodscited by 50
- 2020Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scalingcited by 49
- 2019Differentiable Game Mechanicscited by 43
- 2019A Decentralized Parallel Algorithm for Training Generative Adversarial Netscited by 43
- 2021Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivitycited by 39
- 2019Revisiting Stochastic Extragradientcited by 35
- 2019A Closer Look at the Optimization Landscapes of Generative Adversarial Networkscited by 25
- 2021Decentralized Local Stochastic Extra-Gradient for Variational Inequalitiescited by 25
- 2019ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problemscited by 18
- 2020Accelerating Smooth Games by Manipulating Spectral Shapescited by 18
- 2021On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averagingcited by 18
- 2017YellowFin and the Art of Momentum Tuningcited by 16
- 2022Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicitycited by 16
- 2018Accelerated Gossip in Networks of Given Dimension using Jacobi Polynomial Iterationscited by 15
- 2021Super-Acceleration with Cyclical Step-sizescited by 14
- 2021Complex Momentum for Optimization in Gamescited by 11
- 2022Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Outcited by 11
- 2020Optimal Randomized First-Order Methods for Least-Squares Problemscited by 10
- 2021Provable Super-Convergence with a Large Cyclical Learning Ratecited by 10
- 2016On the Iteration Complexity of Oblivious First-Order Optimization Algorithmscited by 9
- 2020Universal Average-Case Optimality of Polyak Momentumcited by 9
- 2020Average-case Acceleration for Bilinear Games and Normal Matricescited by 5
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