About: *LHOTSE* is a C++ class library designed for the implementation of large, efficient scientific applications in Machine Learning and Statistics. 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: 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: This page contains the implementation used in the paper „Experimental Design for Efficient Identification of Gene Regulatory Networks using Sparse Bayesian Models“ by Florian Steinke, Matthias [...] Changes:Initial Announcement on mloss.org.
|
About: Efficient implementation of penalized multiple logistic regression (aka multi-class) with Mercer kernels, aka MAP approximation to the multi-class Gaussian process model. This includes [...] Changes:Initial Announcement on mloss.org.
|
About: This is a set of MATLAB(R) functions and MEX files which I wrote to make working with this system somewhat bearable. They allow to call BLAS and LAPACK functions, which do very efficient dense [...] Changes:Initial Announcement on mloss.org.
|