112
Voted
JMLR
2006
15 years 1 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...
119
Voted
IJON
2008
15 years 1 months ago
2008
Discovering a representation that allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can ...
117
Voted
ACL
2004
15 years 2 months ago
2004
Aligning words from sentences which are mutual translations is an important problem in different settings, such as bilingual terminology extraction, Machine Translation, or projec...
133
Voted
NIPS
2008
15 years 2 months ago
2008
Principal Components Analysis (PCA) has become established as one of the key tools for dimensionality reduction when dealing with real valued data. Approaches such as exponential ...
111
click to vote
EWCBR
2008
Springer
15 years 2 months ago
2008
Springer
After fifteen years of CBR conferences, this paper sets out to examine the themes that have evolved in CBR research as revealed by the implicit and explicit relationships between t...
120
Voted
CIVR
2008
Springer
15 years 2 months ago
2008
Springer
In information retrieval, sub-space techniques are usually used to reveal the latent semantic structure of a data-set by projecting it to a low dimensional space. Non-negative mat...
118
Voted
SLSFS
2005
Springer
15 years 6 months ago
2005
Springer
Abstract. This article presents a unified theory for analysis of components in discrete data, and compares the methods with techniques such as independent component analysis, non-...
128
Voted
ICA
2007
Springer
15 years 7 months ago
2007
Springer
Discovering a representation that allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can b...
153
Voted
ICASSP
2008
IEEE
15 years 7 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...
99
Voted
ICASSP
2008
IEEE
15 years 7 months ago
2008
IEEE
We describe the underlying probabilistic generative signal model of non-negative matrix factorisation (NMF) and propose a realistic conjugate priors on the matrices to be estimate...