Projects that are tagged with active learning.


Logo BayesOpt, a Bayesian Optimization toolbox 0.6

by rmcantin - March 26, 2014, 17:48:17 CET [ Project Homepage BibTeX Download ] 4383 views, 997 downloads, 2 subscriptions

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:

-Complete refactoring of inner parts of the library. The code is easier to understand/modify and it allow simpler integration with new algorithms.

-Updated to the latest version of NLOPT (2.4.1). Wrapper code symplified.

-Error codes replaced with exceptions in C++ interface. Library is exception safe.

-API modified to support new learning methods for kernel hyperparameters (e.g: MCMC). Warning: config parameters about learning have changed. Code using previous versions might not work. Some of the learning methods (like MCMC) are not yet implemented.

-Added configuration of random numbers (can be fixed for debugging). Fixed issue with random numbers using different sources or random number with potential correlations. Now all the elements are guaranteed to use the same instance of the random engine.

-Improved numerical results (e.g.: hyperparameter optimization is done in log space)

-More examples and tests.

-Fixed bugs.

-The number of inner iterations have been increased by default, so overall optimization time using default configuration might be slower, but with improved results.


Logo JMLR Surrogate Modeling Toolbox 7.0.2

by dgorissen - September 4, 2010, 07:48:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10470 views, 3114 downloads, 1 subscription

About: The SUMO Toolbox is a Matlab toolbox that automatically builds accurate surrogate models (also known as metamodels or response surface models) of a given data source (e.g., simulation code, data set, script, ...) within the accuracy and time constraints set by the user. The toolbox minimizes the number of data points (which it selects automatically) since they are usually expensive.

Changes:

Incremental update, fixing some cosmetic issues, coincides with JMLR publication.


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:
  • Modified specification of optional parameters (using sfo_opt)
  • Added sfo_ls_lazy for maximizing nonnegative submodular functions
  • Added sfo_fn_infogain, sfo_fn_lincomb, sfo_fn_invert, ...
  • Added additional documentation and more examples
  • Now Octave ready

Logo LASVM 1.1

by leonbottou - August 3, 2009, 15:50:30 CET [ Project Homepage BibTeX Download ] 8012 views, 1382 downloads, 0 subscriptions

About: Reference implementation of the LASVM online and active SVM algorithms as described in the JMLR paper. The interesting bit is a small C library that implements the LASVM process and reprocess [...]

Changes:

Minor bug fix