A Stochastic Quasi-Newton Method for Large-Scale Nonconvex Optimization with Applications
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Abstract (arXiv)
This paper proposes a novel stochastic version of damped and regularized BFGS method for addressing the above problems.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Dec 2019.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 2.
4 papers.
- 2024A Differential Geometric View and Explainability of GNN on Evolving Graphscited by 4
- 2021Adaptive First- and Second-Order Algorithms for Large-Scale Machine Learningcited by 1
- 2022A Novel Fast Exact Subproblem Solver for Stochastic Quasi-Newton Cubic Regularized Optimizationcited by 1
- 2024A Stochastic Quasi-Newton Method for Non-convex Optimization with Non-uniform Smoothnesscited by 1
- 2024A Stochastic Quasi-Newton Method for Non-convex Optimization with Non-uniform Smoothness22 Mar 2024
- 2024A Differential Geometric View and Explainability of GNN on Evolving Graphs11 Mar 2024
- 2022A Novel Fast Exact Subproblem Solver for Stochastic Quasi-Newton Cubic Regularized Optimization19 Apr 2022
- 2021Adaptive First- and Second-Order Algorithms for Large-Scale Machine Learning29 Nov 2021