Speaker
Soeren Laue
Description
Optimization is the working horse of machine learning. Our framework (GENO) allows specifying optimization problems in an easy to read modeling language. From such a description a solver is generated automatically, that can solve the specified class of optimization problems. The generated solvers are highly efficient and often outperform hand-written, specialized solvers for machine learning. We will demonstrate the integration of GENO into a typical machine learning workflow on an example from Physics (Raman spectroscopy).
