20 search results - page 3 / 4 » List-wise learning to rank with matrix factorization for col... |
SIAMMAX
2010
13 years 2 months ago
2010
The problem of completing a low-rank matrix from a subset of its entries is often encountered in the analysis of incomplete data sets exhibiting an underlying factor model with app...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such models are usually fitted to data by finding a MAP...
JMLR
2010
13 years 2 months ago
2010
While most popular collaborative filtering methods use low-rank matrix factorization and parametric density assumptions, this article proposes an approach based on distribution-fr...
AAAI
2012
11 years 9 months ago
2012
To solve the sparsity problem in collaborative filtering, researchers have introduced transfer learning as a viable approach to make use of auxiliary data. Most previous transfer...
TIT
2010
13 years 2 months ago
2010
This paper is concerned with the problem of recovering an unknown matrix from a small fraction of its entries. This is known as the matrix completion problem, and comes up in a gr...