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Logo libcmaes 0.9.2

by beniz - October 30, 2014, 14:08:34 CET [ Project Homepage BibTeX Download ] 1977 views, 417 downloads, 3 subscriptions

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.

Changes:

Main changes:

  • new VD-CMA algorithm with linear time and space complexity for black-box optimization

  • API control of stopping criteria, with individual activation scheme

  • improved memory control when tackling large-scale optimization problems

  • solutions now support printing out in pheno space

  • improved API of solutions object

  • fixed compilation error with gcc 4.7


Logo PILCO policy search framework 0.9

by marc - September 27, 2013, 12:45:12 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1964 views, 380 downloads, 1 subscription

About: Data-efficient policy search framework using probabilistic Gaussian process models

Changes:

Initial Announcement on mloss.org.


About: Fast Multidimensional GP Inference using Projected Additive Approximation

Changes:

Initial Announcement on mloss.org.


About: In this paper, we propose an improved principal component analysis based on maximum entropy (MaxEnt) preservation, called MaxEnt-PCA, which is derived from a Parzen window estimation of Renyi’s quadratic entropy. Instead of minimizing the reconstruction error either based on L2-norm or L1-norm, the MaxEnt-PCA attempts to preserve as much as possible the uncertainty information of the data measured by entropy. The optimal solution of MaxEnt-PCA consists of the eigenvectors of a Laplacian probability matrix corresponding to the MaxEnt distribution. MaxEnt-PCA (1) is rotation invariant, (2) is free from any distribution assumption, and (3) is robust to outliers. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed linear method as compared to other related robust PCA methods.

Changes:

Initial Announcement on mloss.org.


Logo Oboe A Chinese Syntactic Parser 1.0

by openpr_nlpr - April 9, 2012, 09:08:35 CET [ Project Homepage BibTeX Download ] 1923 views, 422 downloads, 1 subscription

About: Oboe is a software for Chinese syntactic parsing, and it can display syntactic trees in a graphical view with two kinds of representation: phrase tree and dependency tree. So it is very helpful for NLP researchers, especially for researchers focusing on syntax-based methods.

Changes:

Initial Announcement on mloss.org.


Logo pySPACE 1.2

by krell84 - October 29, 2014, 15:36:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1919 views, 415 downloads, 1 subscription

About: --Signal Processing and Classification Environment in Python using YAML and supporting parallelization-- pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface.

Changes:

improved testing, improved documentation, windows compatibility, more algorithms


Logo BayesPy 0.2.2

by jluttine - November 1, 2014, 11:06:01 CET [ Project Homepage BibTeX Download ] 1914 views, 549 downloads, 3 subscriptions

About: Variational Bayesian inference tools for Python

Changes:
  • Fix normalization of categorical Markov chain probabilities (fixes HMM demo)
  • Fix initialization from parameter values

Logo RLPy 1.3a

by bobklein2 - August 28, 2014, 14:34:35 CET [ Project Homepage BibTeX Download ] 1898 views, 422 downloads, 1 subscription

About: RLPy is a framework for performing reinforcement learning (RL) experiments in Python. RLPy provides a large library of agent and domain components, and a suite of tools to aid in experiments (parallelization, hyperparameter optimization, code profiling, and plotting).

Changes:
  • Fixed bug where results using same random seed were different with visualization turned on/off
  • Created RLPy package on pypi (Available at https://pypi.python.org/pypi/rlpy)
  • Switched from custom logger class to python default
  • Added unit tests
  • Code readability improvements (formatting, variable names/ordering)
  • Restructured TD Learning heirarchy
  • Updated tutorials

About: This code is developed for incorporating a class of linear priors into the regression model.

Changes:

Initial Announcement on mloss.org.


Logo GP RTSS 1.0

by marc - March 21, 2012, 08:43:52 CET [ BibTeX BibTeX for corresponding Paper Download ] 1863 views, 587 downloads, 1 subscription

About: Gaussian process RTS smoothing (forward-backward smoothing) based on moment matching.

Changes:

Initial Announcement on mloss.org.


Showing Items 421-430 of 543 on page 43 of 55: First Previous 38 39 40 41 42 43 44 45 46 47 48 Next Last