129 search results - page 14 / 26 » Self-Paced Learning for Matrix Factorization |
JMLR
2006
13 years 7 months ago
2006
In order to perform object recognition it is necessary to learn representations of the underlying components of images. Such components correspond to objects, object-parts, or fea...
AAAI
2012
11 years 10 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...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We propose a general and efficient algorithm for learning low-rank matrices. The proposed algorithm converges super-linearly and can keep the matrix to be learned in a compact fac...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Principal component analysis (PCA) minimizes the sum of squared errors (L2-norm) and is sensitive to the presence of outliers. We propose a rotational invariant L1-norm PCA (R1-PC...