Approximate FW Algorithm with a novel DMO method over Graph-structured Support Set
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866917847114973184 |
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| author | Pan, Yijian Qiang, Hongjiao |
| author_facet | Pan, Yijian Qiang, Hongjiao |
| contents | In this project, we reviewed a paper that deals graph-structured convex optimization (GSCO) problem with the approximate Frank-Wolfe (FW) algorithm. We analyzed and implemented the original algorithm and introduced some extensions based on that. Then we conducted experiments to compare the results and concluded that our backtracking line-search method effectively reduced the number of iterations, while our new DMO method (Top-g+ optimal visiting) did not make satisfying enough improvements. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_04389 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Approximate FW Algorithm with a novel DMO method over Graph-structured Support Set Pan, Yijian Qiang, Hongjiao Optimization and Control Machine Learning In this project, we reviewed a paper that deals graph-structured convex optimization (GSCO) problem with the approximate Frank-Wolfe (FW) algorithm. We analyzed and implemented the original algorithm and introduced some extensions based on that. Then we conducted experiments to compare the results and concluded that our backtracking line-search method effectively reduced the number of iterations, while our new DMO method (Top-g+ optimal visiting) did not make satisfying enough improvements. |
| title | Approximate FW Algorithm with a novel DMO method over Graph-structured Support Set |
| topic | Optimization and Control Machine Learning |
| url | https://arxiv.org/abs/2411.04389 |