amirabbasasadi/RockyML

⛰️ RockyML - A High-Performance Scientific Computing Framework for Non-smooth Machine Learning Problems

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This framework helps researchers and engineers tackle complex optimization problems where traditional calculus-based methods don't apply, such as those with discrete variables or non-smooth behaviors. You define your problem and desired optimization flow, and it outputs an optimized solution. This is used by scientists, engineers, and machine learning practitioners who work with challenging numerical optimization.

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Use this if you are developing or applying advanced, high-performance optimization algorithms for problems with non-smooth, discrete, or combinatorial characteristics, especially in distributed computing environments.

Not ideal if your optimization problems are well-behaved, smooth, and solvable with standard, off-the-shelf gradient-based methods or if you are not comfortable with C++ programming.

numerical-optimization scientific-computing high-performance-computing distributed-optimization non-smooth-optimization
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 8 / 25

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Stars

20

Forks

2

Language

C++

License

Apache-2.0

Category

cpp-ml-libraries

Last pushed

Apr 07, 2023

Commits (30d)

0

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