20 search results - page 2 / 4 » List-wise learning to rank with matrix factorization for col... |
AAAI
2010
13 years 6 months ago
2010
Matrix factorization is a fundamental technique in machine learning that is applicable to collaborative filtering, information retrieval and many other areas. In collaborative fil...
ICDM
2010
IEEE
13 years 2 months ago
2010
IEEE
Consider a typical recommendation problem. A company has historical records of products sold to a large customer base. These records may be compactly represented as a sparse custom...
SIGKDD
2010
12 years 11 months ago
2010
In recent years, compressive sensing attracts intensive attentions in the field of statistics, automatic control, data mining and machine learning. It assumes the sparsity of the ...
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
Discrete mixed membership modeling and continuous latent factor modeling (also known as matrix factorization) are two popular, complementary approaches to dyadic data analysis. In...
ICML
2003
IEEE
14 years 5 months ago
2003
IEEE
We study the common problem of approximating a target matrix with a matrix of lower rank. We provide a simple and efficient (EM) algorithm for solving weighted low-rank approximat...