Displaying 1 to 13 from 13 results

librec - LibRec: A Leading Java Library for Recommender Systems, see

  •    Java

LibRec (http://www.librec.net) is a Java library for recommender systems (Java version 1.7 or higher required). It implements a suit of state-of-the-art recommendation algorithms, aiming to resolve two classic recommendation tasks: rating prediction and item ranking. A movie recommender system is designed and available here.

sparsepp - A fast, memory efficient hash map for C++

  •    C++

We believe Sparsepp provides an unparalleled combination of performance and memory usage, and will outperform your compiler's unordered_map on both counts. Only Google's dense_hash_map is consistently faster, at the cost of much greater memory usage (especially when the final size of the map is not known in advance, and insertions cause a resizing). This hash map. like Google's dense_hash_map, uses open addressing (meaning that the hash table entries are conceptually stored in a big array, and collisions are not resolved using a linked list, but by probing). A big drawback of open addressing is that when the array needs to be resized larger, the high mark for memory usage is typically 3 times the current map size (as we allocate a new array twice as big as the current one, and copy from the old array to the new one). Sparsepp's implementation resolves this memory usage issue, and the memory usage high mark shows only a small bump when resizing.

Native code wrapping using c# : fsutil sparse commands

  •    CSharp

Ever thought about creating HUGE FILES for future use but felt bad for the wasted memory? Well, SPARSE FILES are the ANSWER! This FSUTIL SPARSE COMMANDS WRAPPING CODE will help any user to create, query, set as and check those files using the convenient c# anguage. Enjoy!

cholesky-solve - [WIP] This module solves sparse symmetric positive definite linear systems by using the Cholesky decomposition

  •    Javascript

This module solves sparse symmetric positive definite linear systems, by finding the Cholesky decomposition(the LDL^T decomposition, and not the LL^T decomposition), and then doing forward substitution and backward substitution. It is basically a Javascript port of the paper "Algorithm 8xx: a concise sparse Cholesky factorization package". This kind of solver has many applications in digital geometry processing.Decomposes M into the Cholesky decomposition of the form LDL^T. A function is returned that can be used to solve the equation Mx = b, for some given value of b.

irf - Incremental Random Forest

  •    C++

The forest is maintained incrementally as samples are added or removed - rather than fully rebuilt from scratch every time - to save effort. It is not a streaming implementation, all the samples are stored and will be reseen when required to recursively rebuild invalidated subtrees. The effort to update each individual tree can vary substantially but the overall effort to update the forest is averaged across the trees so tends not to vary so much.

Sparse-Matrix - C++ implementation of sparse matrix using CRS (Compressed Row Storage) format

  •    C++

C++ implementation of sparse matrix using CRS format. SparseMatrix comes as a template class, so we have to specify the element type.

sparse-structured-attention - Sparse and structured neural attention mechanisms

  •    Python

Efficient implementation of structured sparsity inducing attention mechanisms: fusedmax, oscarmax and sparsemax. Currently available for pytorch v0.2. Requires python (3.6, 3.5, or 2.7), cython, numpy, scipy, scikit-learn, and lightning.

conjugate-gradient - Conjugate gradient solver for JavaScript

  •    Javascript

Solves sparse symmetric positive definite linear systems. These problems arise in many physical applications, like linear elasticity, heat transfer and other diffusion based transport phenomena. This code implements the conjugate gradient method using a Jacobi preconditioner.

count-min-sketch - Count-Min Sketch Data Structure

  •    Javascript

An implementation of Coromode and Muthukrishnan's Count-Min sketch data structure for JavaScript. The count-min sketch is basically a high powered generalization of the bloom filter. While a bloom filter gives an efficient way to approximate membership of a set, a count-min sketch can give approximate data about the relative frequency of items in the set. Creates a count-min sketch data structure.

csr-matrix - Compressed sparse row matrix for node.js

  •    Javascript

A very minimal incremental compressed sparse row matrix library for JavaScript. Turns an array of entries of the form [row, column, value] into a sparse matrix. Note that if there are some zero rows or columns at the end of the matrix, you need to specify the number of rows/columns in the optional nrows/ncols arguments.

neonrvm - Relevance Vector Machine (RVM) Based Machine Learning Library

  •    C

neonrvm is an experimental open source machine learning library for performing regression tasks using RVM technique. It is written in C programming language and comes with bindings for the Python programming language. Under the hood neonrvm uses expectation maximization fitting method, and allows basis functions to be fed incrementally to the model. This helps to keep training times and memory requirements significantly lower for large data sets.

spark-ffm - FFM (Field-Awared Factorization Machine) on Spark

  •    Scala

to fit FFM, that is to extends LIBSVM data format by adding field information to each feature. Currently, we support paralleledSGD and paralledAdagrad optimization methods, as they are more efficient in dealing with large dataset.

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