QUIC and BigQUIC
The QUadratic Inverse Covariance algorithm (latest release 1.1) implements the l1 regularized Gaussian maximum likelihood estimation of the inverse of a covariance matrix.
APM
This MATLAB code trains an Admixture of Poisson MRFs (APM) model using the algorithm described in the associated paper “Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs”. Please see associated papers for more information about the APM model and algorithm.
Divide-and-Conquer Kernel SVM
DC-SVM implements a divide-and-conquer procedure for speeding up kernel SVM training.
LIBPMF
LIBPMF is a library for large-scale parallel matrix factorization. Â Current it implements the CCD++ algorithm, which aims to solve large-scale matrix factorization problems for recommender systems. The software supports several programming languages (e.g., C/C++, Matlab, Python, and R).
Inductive Matrix Completion
Inductive Matrix Completion (IMC) is an algorithm for recommender systems with side-information of users and items. The IMC formulation incorporates features associated with rows (users) and columns (items) in matrix completion, so that it enables predictions for users or items that were not seen during training, and for which only features are known but …
NEO-K-Means
We propose a simple and intuitive objective function that captures the issues of overlap and non-exhaustiveness in a unified manner. Our objective function can be viewed as a reformulation of the traditional k-means objective, with easy-to-understand parameters that capture the degrees of overlap and non-exhaustiveness. To optimize the objective, we propose …
NOMAD
NOMAD is the alias for Non-locking, stOchastic Multi-machine framework for Asynchronous and Decentralized computation. This is a scalable distributed framework for various latent variable models. We have successfully applied NOMAD to two applications: Low-rank Matrix Factorization for Large-scale Recommender Systems Collapsed Gibbs Sampling for Large-…
Graclus
Graclus (latest:Â Version 1.2) is a fast graph clustering software that computes normalized cut and ratio association for a given undirected graph without any eigenvector computation. This is possible because of the mathematical equivalence between general cut or association objectives (including normalized cut and ratio association) and the weighted kernelÂ…