56 search results - page 3 / 12 » On Matrix Representations of Participation Constraints |
115
Voted
ISCAS
2008
IEEE
15 years 3 months ago
2008
IEEE
— Non-negative matrix factorization (NMF), i.e. V ≈ WH where both V, W and H are non-negative has become a widely used blind source separation technique due to its part based r...
UAI
2008
14 years 11 months ago
2008
We introduce Clique Matrices as an alternative representation of undirected graphs, being a generalisation of the incidence matrix representation. Here we use clique matrices to d...
120
click to vote
ICASSP
2008
IEEE
15 years 4 months ago
2008
IEEE
Non-negative matrix factorisation (NMF) is an unsupervised learning technique that decomposes a non-negative data matrix into a product of two lower rank non-negative matrices. Th...
GRAPHICSINTERFACE
2003
14 years 11 months ago
2003
The high dimensionality of the BRDF makes it difficult to use measured data for hardware rendering. Common solutions to overcome this problem include expressing a BRDF as a sum o...
ICPR
2010
IEEE
14 years 7 months ago
2010
IEEE
In this paper, an easily implemented semi-supervised graph learning method is presented for dimensionality reduction and clustering, using the most of prior knowledge from limited...