About: BayesOpt is an efficient, C++ implementation of the Bayesian optimization methodology for nonlinear-optimization, experimental design and stochastic bandits. In the literature it is also called Sequential Kriging Optimization (SKO) or Efficient Global Optimization (EGO). There are also interfaces for C, Matlab/Octave and Python.Changes:
-Improved and extended documentation.
-Extended and simplified API accross platforms.
-Extended functionality (new surrogate functions, new priors, new kernels, new criteria).
-Improved modularity of the optimization process to allow plotting and debugging of intermediate steps.
-Added more demos and examples.
About: This toolbox provides functions for maximizing and minimizing submodular set functions, with applications to Bayesian experimental design, inference in Markov Random Fields, clustering and others.Changes: