Incremental Gauss--Newton Methods with Superlinear Convergence Rates
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Abstract (arXiv)
This paper addresses the challenge of solving large-scale nonlinear equations with H"older continuous Jacobians. We introduce a novel Incremental Gauss--Newton (IGN) method within explicit superlinear convergence rate, which outperforms existing methods that only achieve linear convergence rate. In particular, we formulate our problem by the nonlinear least squares with finite-sum structure, and our method incrementally iterates with the information of one component in each round. We also provide a mini-batch extension to our IGN method that obtains an even faster superlinear convergence rate. Furthermore, we conduct numerical experiments to show the advantages of the proposed methods.
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References · 20
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- 2023Online Learning Guided Curvature Approximation: A Quasi-Newton Method with Global Non-Asymptotic Superlinear Convergencecited by 11
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- 2021Quasi-Newton Methods for Saddle Point Problems and Beyondcited by 10
- 2014A globally convergent incremental Newton methodcited by 5
- 2021A Proximal Quasi-Newton Trust-Region Method for Nonsmooth Regularized Optimizationcited by 4
- 2023Communication Efficient Distributed Newton Method with Fast Convergence Ratescited by 4
- 2021Explicit Superlinear Convergence Rates of Broyden's Methods in Nonlinear Equationscited by 3
- 2021Greedy and Random Broyden's Methods with Explicit Superlinear Convergence Rates in Nonlinear Equationscited by 3
- 2024Incremental Quasi-Newton Methods with Faster Superlinear Convergence Ratescited by 2
- 2023Sharpened Lazy Incremental Quasi-Newton Methodcited by 1
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