<--- Back to Details
First PageDocument Content
Recommender systems / Matrix theory / Linear algebra / Sparse matrices / Multivariate statistics / Non-negative matrix factorization / Collaborative filtering / GroupLens Research / MovieLens / Singular value decomposition / Graph partition / Matrix decomposition
Date: 2015-03-02 08:17:50
Recommender systems
Matrix theory
Linear algebra
Sparse matrices
Multivariate statistics
Non-negative matrix factorization
Collaborative filtering
GroupLens Research
MovieLens
Singular value decomposition
Graph partition
Matrix decomposition

A General Collaborative Filtering Framework based on Matrix Bordered Block Diagonal Forms Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma State Key Laboratory of Intelligent Technology and Systems Department of Compute

Add to Reading List

Source URL: yongfeng.me

Download Document from Source Website

File Size: 633,85 KB

Share Document on Facebook

Similar Documents

Week 6 (due May 14) Reading: Srednicky, sectionIn this exercise you will apply the Faddeev-Popov procedure to simplify some finite-dimensional integrals over spaces of matrices. Such integrals are known as matrix

Week 6 (due May 14) Reading: Srednicky, sectionIn this exercise you will apply the Faddeev-Popov procedure to simplify some finite-dimensional integrals over spaces of matrices. Such integrals are known as matrix

DocID: 1v5Qz - View Document

Geometry of Neural Network Loss Surfaces via Random Matrix Theory  Jeffrey Pennington 1 Yasaman Bahri 1 Abstract Understanding the geometry of neural network

Geometry of Neural Network Loss Surfaces via Random Matrix Theory Jeffrey Pennington 1 Yasaman Bahri 1 Abstract Understanding the geometry of neural network

DocID: 1v21M - View Document

Understanding and Improving Deep Learning with Random Matrix Theory Jeffrey Pennington Google Brain, NYC  November 8, 2017

Understanding and Improving Deep Learning with Random Matrix Theory Jeffrey Pennington Google Brain, NYC November 8, 2017

DocID: 1uOTm - View Document

Week 6 (due Feb. 19) Reading: Srednicki, sectionsNB: In the following problems it is better to use FeynCalc package for Mathematica than to do gamma-matrix traces by hand. See http://www.feyncalc.org/ for detaile

Week 6 (due Feb. 19) Reading: Srednicki, sectionsNB: In the following problems it is better to use FeynCalc package for Mathematica than to do gamma-matrix traces by hand. See http://www.feyncalc.org/ for detaile

DocID: 1uHIP - View Document

Compressed Sensing Theory Projection Matrix Theory

Compressed Sensing Theory Projection Matrix Theory

DocID: 1uwVY - View Document