All entries.
Showing Items 21-30 of 537 on page 3 of 54: Previous 1 2 3 4 5 6 7 8 Next Last

Logo pyGPs 1.2

by mn - July 17, 2014, 10:28:55 CET [ Project Homepage BibTeX Download ] 1704 views, 414 downloads, 2 subscriptions

About: pyGPs is a Python package for Gaussian process (GP) regression and classification for machine learning.

Changes:

Changelog pyGPs v1.2

June 30th 2014

structural updates:

  • input target now can either be in 2-d array with size (n,1) or in 1-d array with size (n,)
  • setup.py updated
  • "import pyGPs" instead of "from pyGPs.Core import gp"
  • rename ".train()" to ".optimize()"
  • rename "Graph-stuff" to "graphExtension"
  • rename kernelOnGraph to "nodeKernels" and graphKernel to "graphKernels"
  • redundancy removed for model.setData(x,y)
  • rewrite "mean.proceed()" to "getMean()" and "getDerMatrix()"
  • rewrite "cov.proceed()" to "getCovMatrix()" and "getDerMatrix()"
  • rename cov.LIN to cov.Linear (to be consistent with mean.Linear)
  • rename module "valid" to "validation"
  • add graph dataset Mutag in python file. (.npz and .mat)
  • add graphUtil.nomalizeKernel()
  • fix number of iteration problem in graphKernels "PropagationKernel"
  • add unit testing for covariance, mean functions

bug fixes:

  • derivatives for cov.LINard
  • derivative of the scalar for cov.covScale
  • demo_GPR_FITC.py missing pyGPs.mean

July 8th 2014

structural updates:

  • add hyperparameter(signal variance s2) for linear covariance
  • add unit testing for inference,likelihood functions as well as models
  • NOT show(print) "maximum number of sweep warning in inference EP" any more
  • documentation updated

bug fixes:

  • typos in lik.Laplace
  • derivative in lik.Laplace

July 14th 2014

documentation updates:

  • online docs updated
  • API file updated

structural updates:

  • made private for methods that users don't need to call

Logo Crino 1.0.0

by jlerouge - July 16, 2014, 17:54:55 CET [ Project Homepage BibTeX Download ] 393 views, 71 downloads, 2 subscriptions

About: Crino: a neural-network library based on Theano

Changes:

1.0.0 (7 july 2014) : - Initial release of crino - Implements a torch-like library to build artificial neural networks (ANN) - Provides standard implementations for : * auto-encoders * multi-layer perceptrons (MLP) * deep neural networks (DNN) * input output deep architecture (IODA) - Provides a batch-gradient backpropagation algorithm, with adaptative learning rate


Logo ABACOC Adaptive Ball Cover for Classification 1.0

by kikot - July 14, 2014, 16:27:03 CET [ BibTeX BibTeX for corresponding Paper Download ] 431 views, 99 downloads, 3 subscriptions

About: Online Action Recognition via Nonparametric Incremental Learning. Java and Matlab code already available. A Python version and the Java source code will be released soon.

Changes:

Initial release of the library, future changes will be advertised shortly.


Logo ARTOS Adaptive Realtime Object Detection System 1.0

by erik - July 11, 2014, 22:02:34 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 521 views, 83 downloads, 2 subscriptions

About: ARTOS can be used to quickly learn models for visual object detection without having to collect a set of samples manually. To make this possible, it uses ImageNet, a large image database with more than 20,000 categories.

Changes:

Initial Announcement on mloss.org.


Logo RankSVM NC 1.0

by rflamary - July 10, 2014, 15:51:21 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 527 views, 114 downloads, 1 subscription

About: This package is an implementation of a linear RankSVM solver with non-convex regularization.

Changes:

Initial Announcement on mloss.org.


Logo PyStruct 0.2

by t3kcit - July 9, 2014, 09:29:23 CET [ Project Homepage BibTeX Download ] 1457 views, 418 downloads, 1 subscription

About: PyStruct is a framework for learning structured prediction in Python. It has a modular interface, similar to the well-known SVMstruct. Apart from learning algorithms it also contains model formulations for popular CRFs and interfaces to many inference algorithm implementation.

Changes:

Initial Announcement on mloss.org.


Logo Semi Stochastic Gradient Descent 1.0

by konkey - July 9, 2014, 04:28:47 CET [ BibTeX BibTeX for corresponding Paper Download ] 476 views, 106 downloads, 1 subscription

About: Efficient implementation of Semi-Stochastic Gradient Descent algorithm (S2GD) for training logistic regression (L2-regularized).

Changes:

Initial Announcement on mloss.org.


Logo IPCA v0.1

by kiraly - July 7, 2014, 10:25:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 534 views, 97 downloads, 1 subscription

About: This package implements Ideal PCA in MATLAB. Ideal PCA is a (cross-)kernel based feature extraction algorithm which is (a) a faster alternative to kernel PCA and (b) a method to learn data manifold certifying features.

Changes:

Initial Announcement on mloss.org.


Logo Encog Machine Learning Framework 3.2

by jeffheaton - July 5, 2014, 23:47:06 CET [ Project Homepage BibTeX Download ] 2566 views, 562 downloads, 1 subscription

About: Encog is a Machine Learning framework for Java, C#, Javascript and C/C++ that supports SVM's, Genetic Programming, Bayesian Networks, Hidden Markov Models and other algorithms.

Changes:

Changes for Encog 3.2:

Issue #53: Fix Out Of Range Bug In BasicMLSequenceSet. Issue #52: Unhandled exception in Encog.Util.File.ResourceLoader.CreateStream (ResourceLoader.cs) Issue #50: Concurrency bugs in PruneIncremental Issue #48: Unit Tests Failing - TestHessian Issue #46: Couple of small fixes - Temporal DataSet and SCG training Issue #45: Fixed EndMinutesStrategy to correctly evaluate ShouldStop after the specified number of minutes have elapsed. Issue #44: Encog.ML.Data.Basic.BasicMLDataPairCentroid.Add() & .Remove() Issue #43: Unit Tests Failing - Matrix not full rank Issue #42: Nuget - NuSpec Issue #36: Load Examples easier


Logo JMLR MSVMpack 1.5

by lauerfab - July 3, 2014, 16:02:49 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10696 views, 3682 downloads, 2 subscriptions

About: MSVMpack is a Multi-class Support Vector Machine (M-SVM) package. It is dedicated to SVMs which can handle more than two classes without relying on decomposition methods and implements the four M-SVM models from the literature: Weston and Watkins M-SVM, Crammer and Singer M-SVM, Lee, Lin and Wahba M-SVM, and the M-SVM2 of Guermeur and Monfrini.

Changes:
  • Windows binaries are now included (by Emmanuel Didiot)
  • MSVMpack can now be compiled on Windows (by Emmanuel Didiot)
  • Fixed polynomial kernel
  • Minor bug fixes

Showing Items 21-30 of 537 on page 3 of 54: Previous 1 2 3 4 5 6 7 8 Next Last