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» The structure of intrinsic complexity of learning
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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
RE
2002
Springer
13 years 7 months ago
Requirements Engineering in the Health Care Domain
There are many different approaches to elicit requirements each having its strengths and weaknesses. Hence, some approaches may be ore suitable to one domain then another. Moreove...
Luiz Marcio Cysneiros
CVPR
2009
IEEE
15 years 2 months ago
Learning Visual Flows: A Lie Algebraic Approach
We present a novel method for modeling dynamic visual phenomena, which consists of two key aspects. First, the in- tegral motion of constituent elements in a dynamic scene is ca...
Dahua Lin, W. Eric L. Grimson, John W. Fisher III
ECCV
2010
Springer
13 years 10 months ago
Clustering Complex Data with Group-Dependent Feature Selection
Abstract. We describe a clustering approach with the emphasis on detecting coherent structures in a complex dataset, and illustrate its effectiveness with computer vision applicat...
NIPS
2007
13 years 9 months ago
Random Projections for Manifold Learning
We propose a novel method for linear dimensionality reduction of manifold modeled data. First, we show that with a small number M of random projections of sample points in RN belo...
Chinmay Hegde, Michael B. Wakin, Richard G. Barani...