mlsanityData to 14 Oct 2026

Polyak's Heavy Ball Method Achieves Accelerated Local Rate of Convergence under Polyak-Lojasiewicz Inequality

arXiv 2410.16849 ↗First posted 22 Oct 2024math.OC cs.LGcited by 3

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Abstract (arXiv)

In this work, we analyze the convergence of Polyak's heavy ball method in both continuous and discrete time for non-convex C4-objective functions satisfying the Polyak-Lojasiewicz inequality. Under this weak assumption, we recover the asymptotic convergence rates originally derived by Polyak in [Polyak, U.S.S.R. Comput. Math. and Math. Phys., 1964] for strongly convex objectives. Our results demonstrate that the heavy ball method exhibits asymptotic local acceleration on this class of functions. In particular, in the discrete time setting, we prove local convergence of the iterates to a minimum once the method enters a sufficiently small neighborhood of the set of minima, for a broad range of hyperparameters, including aggressive choices for the momentum parameter and the step-size for which global convergence is known to fail. Instead of the usually employed Lyapunov-type arguments, our approach leverages a new differential geometric perspective of the Polyak-Lojasiewicz inequality proposed in [Rebjock and Boumal, Math. Program., 2025].

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 28 of its 64 references that are in the map. First posted on arXiv 22 Oct 2024.

Builds on

28 of 64 references.

References · 28

  1. 2016Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Lojasiewicz Conditioncited by 539
  2. 2015A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insightscited by 206
  3. 2014Analysis and Design of Optimization Algorithms via Integral Quadratic Constraintscited by 105
  4. 2019Convergence rates for the stochastic gradient descent method for non-convex objective functionscited by 66
  5. 2014Global convergence of the Heavy-ball method for convex optimizationcited by 61
  6. 2015From error bounds to the complexity of first-order descent methods for convex functionscited by 43
  7. 2021Stochastic gradient descent with noise of machine learning type. Part I: Discrete time analysiscited by 39
  8. 2014iPiano: Inertial Proximal Algorithm for Non-Convex Optimizationcited by 30
  9. 2021Convergence of stochastic gradient descent schemes for Lojasiewicz-landscapescited by 28
  10. 2020A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Networkcited by 19
  11. 2016Fast convex optimization via inertial dynamics with Hessian driven dampingcited by 13
  12. 2021On minimal representations of shallow ReLU networkscited by 13
16 more
  1. 2023Provable non-accelerations of the heavy-ball methodcited by 12
  2. 2021Convergence rates for the Heavy-Ball continuous dynamics for non-convex optimization, under Polyak-L ojasiewicz conditioncited by 11
  3. 2022Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Lojasiewicz Functions when the Non-Convexity is Averaged-Outcited by 11
  4. 2016Local Convergence of the Heavy-ball Method and iPiano for Non-convex Optimizationcited by 9
  5. 2018Non-monotone Behavior of the Heavy Ball Methodcited by 8
  6. 2017Convergence of the Forward-Backward Algorithm: Beyond the Worst Case with the Help of Geometrycited by 7
  7. 2024Nesterov acceleration in benignly non-convex landscapescited by 7
  8. 2019Accelerated First-Order Methods: Differential Equations and Lyapunov Functionscited by 5
  9. 2024Almost sure convergence rates of stochastic gradient methods under gradient dominationcited by 5
  10. 2016A Multi-step Inertial Forward--Backward Splitting Method for Non-convex Optimizationcited by 3
  11. 2022On the Lower Bound of Minimizing Polyak-Lojasiewicz Functionscited by 3
  12. 2021Inertial Newton Algorithms Avoiding Strict Saddle Pointscited by 2
  13. 2022Gradient-Type Methods for Optimization Problems with Polyak-Lojasiewicz Condition: Early Stopping and Adaptivity to Inexactness Parametercited by 2
  14. 2024Heavy Ball Momentum for Non-Strongly Convex Optimizationcited by 2
  15. 2013Second-order growth, tilt stability, and metric regularity of the subdifferentialcited by 1
  16. 2013Quadratic growth and critical point stability of semi-algebraic functionscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.