19 search results - page 2 / 4 » Sparse Non-Negative Matrix Factorization for Mesh Segmentati... |
CORR
2004
Springer
13 years 5 months ago
2004
Springer
Non-negative matrix factorization (NMF) is a recently developed technique for finding parts-based, linear representations of non-negative data. Although it has successfully been a...
ICIP
2009
IEEE
14 years 6 months ago
2009
IEEE
In this paper, we present a novel algorithm for representing facial expressions. The algorithm is based on the non-negative matrix factorization (NMF) algorithm, which decomposes ...
CORR
2002
Springer
13 years 5 months ago
2002
Springer
Abstract. Non-negative sparse coding is a method for decomposing multivariate data into non-negative sparse components. In this paper we briefly describe the motivation behind this...
JMLR
2010
13 years 4 months ago
2010
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
ECCV
2006
Springer
14 years 7 months ago
2006
Springer
Non-negative tensor factorization (NTF) has recently been proposed as sparse and efficient image representation (Welling and Weber, Patt. Rec. Let., 2001). Until now, sparsity of t...