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» Information Theory, Inference, and Learning Algorithms
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NIPS
2007
13 years 9 months ago
Retrieved context and the discovery of semantic structure
Semantic memory refers to our knowledge of facts and relationships between concepts. A successful semantic memory depends on inferring relationships between items that are not exp...
Vinayak Rao, Marc Howard
FOCI
2007
IEEE
14 years 2 months ago
Almost All Learning Machines are Singular
— A learning machine is called singular if its Fisher information matrix is singular. Almost all learning machines used in information processing are singular, for example, layer...
Sumio Watanabe
MM
2004
ACM
248views Multimedia» more  MM 2004»
14 years 1 months ago
Incremental semi-supervised subspace learning for image retrieval
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Xiaofei He
JAIR
2006
110views more  JAIR 2006»
13 years 8 months ago
Domain Adaptation for Statistical Classifiers
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
Hal Daumé III, Daniel Marcu
ICCV
2005
IEEE
14 years 1 months ago
Perceptual Scale Space and its Applications
When an image is viewed at varying resolutions, it is known to create discrete perceptual jumps or transitions amid the continuous intensity changes. In this paper, we study a per...
Yizhou Wang, Siavosh Bahrami, Song Chun Zhu