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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.02155 |
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| _version_ | 1866913719718510592 |
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| author | Buck, Kevin Babyak, Jessica Piersanti, Paolo Zumbrun, Kevin Gallos, Christiane Gallos, Dorothea |
| author_facet | Buck, Kevin Babyak, Jessica Piersanti, Paolo Zumbrun, Kevin Gallos, Christiane Gallos, Dorothea |
| contents | We review convergence and behavior of stochastic gradient descent for convex and nonconvex optimization, establishing various conditions for convergence to zero of the variance of the gradient of the objective function, and presenting a number of simple examples demonstrating the approximate evolution of the probability density under iteration, including applications to both classical two-player and asynchronous multiplayer games |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_02155 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Nonconvex optimization and convergence of stochastic gradient descent, and solution of asynchronous game Buck, Kevin Babyak, Jessica Piersanti, Paolo Zumbrun, Kevin Gallos, Christiane Gallos, Dorothea Optimization and Control We review convergence and behavior of stochastic gradient descent for convex and nonconvex optimization, establishing various conditions for convergence to zero of the variance of the gradient of the objective function, and presenting a number of simple examples demonstrating the approximate evolution of the probability density under iteration, including applications to both classical two-player and asynchronous multiplayer games |
| title | Nonconvex optimization and convergence of stochastic gradient descent, and solution of asynchronous game |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2503.02155 |