About: A Deep Learning API and server

Initial Announcement on mloss.org.

About: Libcmaes is a multithreaded C++11 library (with Python bindings) for high performance blackbox stochastic optimization of difficult, possibly non-linear and non-convex functions, using the CMA-ES algorithm for Covariance Matrix Adaptation Evolution Strategy. Libcmaes is useful to minimize / maximize any function, without information regarding gradient or derivability.

This is a major release, with several novelties, improvements and fixes, among which:

• step-size two-point adaptaion scheme for improved performances in some settings, ref #88

• important bug fixes to the ACM surrogate scheme, ref #57, #106

• simple high-level workflow under Python, ref #116

• improved performances in high dimensions, ref #97

• improved profile likelihood and contour computations, including under geno/pheno transforms, ref #30, #31, #48

• elitist mechanism for forcing best solutions during evolution, ref 103

• new legacy plotting function, ref #110

• optional initial function value, ref #100

• improved C++ API, ref #89

• Python bindings support with Anaconda, ref #111

• configure script now tries to detect numpy when building Python bindings, ref #113

• Python bindings now have embedded documentation, ref #114

• support for Travis continuous integration, ref #122

• lower resolution random seed initialization