GENO – Optimization for Classical Machine Learning Made Fast and Easy
2020 ◽
Vol 34
(09)
◽
pp. 13620-13621
Keyword(s):
Most problems from classical machine learning can be cast as an optimization problem. We introduce GENO (GENeric Optimization), a framework that lets the user specify a constrained or unconstrained optimization problem in an easy-to-read modeling language. GENO then generates a solver, i.e., Python code, that can solve this class of optimization problems. The generated solver is usually as fast as hand-written, problem-specific, and well-engineered solvers. Often the solvers generated by GENO are faster by a large margin compared to recently developed solvers that are tailored to a specific problem class.An online interface to our framework can be found at http://www.geno-project.org.
1998 ◽
Vol 2
(6)
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pp. 208-213
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2019 ◽
Vol 38
(4)
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2018 ◽
Vol 332
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pp. 012024
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1976 ◽
Vol 16
(3)
◽
pp. 40-51
2003 ◽
Vol 02
(01)
◽
pp. 41-70
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