optHIM: Hybrid Iterative Methods for Continuous Optimization in PyTorch
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909603094069248 |
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| author | Sridhar, Nikhil Shah, Sajiv |
| author_facet | Sridhar, Nikhil Shah, Sajiv |
| contents | We introduce optHIM, an open-source library of continuous unconstrained optimization algorithms implemented in PyTorch for both CPU and GPU. By leveraging PyTorch's autograd, optHIM seamlessly integrates function, gradient, and Hessian information into flexible line-search and trust-region methods. We evaluate eleven state-of-the-art variants on benchmark problems spanning convex and non-convex landscapes. Through a suite of quantitative metrics and qualitative analyses, we demonstrate each method's strengths and trade-offs. optHIM aims to democratize advanced optimization by providing a transparent, extensible, and efficient framework for research and education. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_04137 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | optHIM: Hybrid Iterative Methods for Continuous Optimization in PyTorch Sridhar, Nikhil Shah, Sajiv Mathematical Software Optimization and Control We introduce optHIM, an open-source library of continuous unconstrained optimization algorithms implemented in PyTorch for both CPU and GPU. By leveraging PyTorch's autograd, optHIM seamlessly integrates function, gradient, and Hessian information into flexible line-search and trust-region methods. We evaluate eleven state-of-the-art variants on benchmark problems spanning convex and non-convex landscapes. Through a suite of quantitative metrics and qualitative analyses, we demonstrate each method's strengths and trade-offs. optHIM aims to democratize advanced optimization by providing a transparent, extensible, and efficient framework for research and education. |
| title | optHIM: Hybrid Iterative Methods for Continuous Optimization in PyTorch |
| topic | Mathematical Software Optimization and Control |
| url | https://arxiv.org/abs/2505.04137 |