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ScalingOpt | Welcome to join and co-build the Optimization Community!
ScalingOpt is a professional platform focusing on optimization for large-scale deep learning, aiming to advocate for "Optimization at Scale," which means verifiable and scalable optimization algorithms.
This community platform is dedicated to gathering, discovering, comparing, and contributing various cutting-edge optimizers and optimization algorithms.
It's not just a simple Awesome List, it also includes:
Visualizations: Covers visualization scripts for the Rosenbrock Function and the Rastrigin Function for users to freely explore.
Benchmark: We recommend Algoperf as the primary source, along with other verifiable benchmarks and analysis articles, for users to reference the best optimizer.
Papers & Blogs Recommendation: The platform summarizes high-quality papers and blogs from recent years, and continuously adds the latest papers based on daily arXiv updates, currently totaling nearly a hundred articles.
Tutorials Sharing: The platform collects quality resources from the community and is independently producing a "From Classical to Modern Optimizers" Tutorial Series, which is expected to be updated by the end of the month.
We welcome everyone to use it and provide valuable feedback. We also welcome you to join us in co-building the community and focusing on the latest developments in optimization algorithms. The ScalingOpt community platform will be continuously updated.
We hope everyone can give ScalingOpt a star ⭐️. Thank you very much 🙏
Website: https://tianshijing.github.io/ScalingOpt
Github: https://github.com/tianshijing/ScalingOpt
ScalingOpt is a professional platform focusing on optimization for large-scale deep learning, aiming to advocate for "Optimization at Scale," which means verifiable and scalable optimization algorithms.
This community platform is dedicated to gathering, discovering, comparing, and contributing various cutting-edge optimizers and optimization algorithms.
It's not just a simple Awesome List, it also includes:
Visualizations: Covers visualization scripts for the Rosenbrock Function and the Rastrigin Function for users to freely explore.
Benchmark: We recommend Algoperf as the primary source, along with other verifiable benchmarks and analysis articles, for users to reference the best optimizer.
Papers & Blogs Recommendation: The platform summarizes high-quality papers and blogs from recent years, and continuously adds the latest papers based on daily arXiv updates, currently totaling nearly a hundred articles.
Tutorials Sharing: The platform collects quality resources from the community and is independently producing a "From Classical to Modern Optimizers" Tutorial Series, which is expected to be updated by the end of the month.
We welcome everyone to use it and provide valuable feedback. We also welcome you to join us in co-building the community and focusing on the latest developments in optimization algorithms. The ScalingOpt community platform will be continuously updated.
We hope everyone can give ScalingOpt a star ⭐️. Thank you very much 🙏
Website: https://tianshijing.github.io/ScalingOpt
Github: https://github.com/tianshijing/ScalingOpt
