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About: The Chestnut Machine Learning Library is a suite of machine learning algorithms written in Python with some code written in C for efficiency. Most algorithms are called with a simple, functional API [...] Changes:Initial Announcement on mloss.org.

About: OLaRank is an online solver of the dual formulation of support vector machines for sequence labeling using viterbi decoding. Changes:Initial Announcement on mloss.org.

About: The incomplete Cholesky decomposition for a dense symmetric positive definite matrix A is a simple way of approximating A by a matrix of low rank (you can choose the rank). It has been used [...] Changes:Initial Announcement on mloss.org.

About: The package provides a Lagrangian approach to the posterior regularization of given linear mappings. This is important in two cases, (a) when systems are underdetermined and (b) when the external model for calculating the mapping is invariant to properties such as scaling. The software may be applied in cases when the external model does not provide its own regularization strategy. In addition, the package allows to rank attributes according to their distortion potential to a given linear mapping. Changes:Version 1.1 (May 23, 2012) memory and time optimizations distderivrel.m now supports assessing the relevance of attribute pairs Version 1.0 (Nov 9, 2011) * Initial Announcement on mloss.org.

About: Tekkotsu is a highlevel framework for robot programming that provides primitives for perception, manipulation, navigation, and control. It supports a variety of robot platforms. Changes:Initial Announcement on mloss.org.

About: stroll (STRuctured Output Learning Library) is a library for Structured Output Learning. Changes:Initial Announcement on mloss.org.

About: You should never compute, maintain, or update the inverse of a symmetric positive definite matrix if you do not have to. Computing the inverse or manipulating it is inherently instable. You can [...] Changes:Initial Announcement on mloss.org.

About: redsvd is a library for solving several matrix decomposition (SVD, PCA, eigen value decomposition) redsvd can handle very large matrix efficiently, and optimized for a truncated SVD of sparse matrices. For example, redsvd can compute a truncated SVD with top 20 singular values for a 100K x 100K matrix with 10M nonzero entries in about two second. Changes:Initial Announcement on mloss.org.

About: markov thebeast is a Markov Logic interpreter. We also see it as structured prediction framework in which the user can define a loglinear distribution over a complex output space. Changes:Initial Announcement on mloss.org.

About: OLaRankGreedy is an online solver of the dual formulation of support vector machines for sequence labeling using greedy inference. Changes:Initial Announcement on mloss.org.
