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About: This is demo program on global thresholding for image of bright small objects, such as aircrafts in airports. the program include four method, otsu,2DTsallis,PSSIM, Smoothnees Method. Changes:Initial Announcement on mloss.org.

About: Nonnegative Sparse Coding, Discriminative Semisupervised Learning, sparse probability graph Changes:Initial Announcement on mloss.org.

About: DRVQ is a C++ library implementation of dimensionalityrecursive vector quantization, a fast vector quantization method in highdimensional Euclidean spaces under arbitrary data distributions. It is an approximation of kmeans that is practically constant in data size and applies to arbitrarily high dimensions but can only scale to a few thousands of centroids. As a byproduct of training, a tree structure performs either exact or approximate quantization on trained centroids, the latter being not very precise but extremely fast. Changes:Initial Announcement on mloss.org.

About: The toolbox is to calculate normalized information measures from a given m by (m+1) confusion matrix for objective evaluations of an abstaining classifier. It includes total 24 normalized information measures based on three groups of definitions, that is, mutual information, information divergence, and cross entropy. Changes:Initial Announcement on mloss.org.

About: A Java Toolbox for Scalable Probabilistic Machine Learning. Changes:
Detailed information can be found in the toolbox's web page

About: Loglinear analysis for highdimensional data Changes:Initial Announcement on mloss.org.

About: A library for calculating and accessing generalized Stirling numbers of the second kind, which are used for inference in PoissonDirichlet processes. Changes:Initial Announcement on mloss.org.

About: It's a C++ program for symmetric matrix diagonalization, inversion and principal component anlaysis(PCA). The matrix diagonalization function can also be applied to the computation of singular value decomposition (SVD), Fisher linear discriminant analysis (FLDA) and kernel PCA (KPCA) if forming the symmetric matrix appropriately. Changes:Initial Announcement on mloss.org.

About: Distributed optimization: Support Vector Machines and LASSO regression on distributed data Changes:Initial Upload

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.
