Sciweavers

Share
65 search results - page 2 / 13
» Learning a Bi-Stochastic Data Similarity Matrix
Sort
View
CVPR
2006
IEEE
13 years 8 months ago
Spectral Methods for Automatic Multiscale Data Clustering
Spectral clustering is a simple yet powerful method for finding structure in data using spectral properties of an associated pairwise similarity matrix. This paper provides new in...
Arik Azran, Zoubin Ghahramani
ICPR
2008
IEEE
13 years 7 months ago
A matrix alignment approach for link prediction
This paper introduces a new discriminative learning technique for link prediction based on the matrix alignment approach. Our algorithm automatically determines the most predictiv...
Jerry Scripps, Pang-Ning Tan, Feilong Chen, Abdol-...
ICML
2002
IEEE
13 years 6 months ago
Learning the Kernel Matrix with Semi-Definite Programming
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
UAI
2003
12 years 7 months ago
Learning Generative Models of Similarity Matrices
Recently, spectral clustering (a.k.a. normalized graph cut) techniques have become popular for their potential ability at ļ¬nding irregularlyshaped clusters in data. The input to...
Rómer Rosales, Brendan J. Frey
ICASSP
2008
IEEE
13 years 13 days ago
Unsupervised learning of auditory filter banks using non-negative matrix factorisation
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...
Alexander Bertrand, Kris Demuynck, Veronique Stout...
books