65 search results - page 2 / 13 » Learning a Bi-Stochastic Data Similarity Matrix |
125
Voted
CVPR
2006
IEEE
16 years 5 months ago
2006
IEEE
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...
109
Voted
ICPR
2008
IEEE
16 years 4 months ago
2008
IEEE
This paper introduces a new discriminative learning technique for link prediction based on the matrix alignment approach. Our algorithm automatically determines the most predictiv...
149
Voted
ICML
2002
IEEE
16 years 4 months ago
2002
IEEE
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...
161
Voted
UAI
2003
15 years 5 months ago
2003
Recently, spectral clustering (a.k.a. normalized graph cut) techniques have become popular for their potential ability at finding irregularlyshaped clusters in data. The input to...
186
Voted
ICASSP
2008
IEEE
15 years 10 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...