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» Unsupervised Learning of Part-Based Representations
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TNN
2010
143views Management» more  TNN 2010»
14 years 4 months ago
Using unsupervised analysis to constrain generalization bounds for support vector classifiers
Abstract--A crucial issue in designing learning machines is to select the correct model parameters. When the number of available samples is small, theoretical sample-based generali...
Sergio Decherchi, Sandro Ridella, Rodolfo Zunino, ...
NECO
2010
154views more  NECO 2010»
14 years 8 months ago
Role of Homeostasis in Learning Sparse Representations
Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the emergence of this response is to state that ...
Laurent U. Perrinet
CVPR
2007
IEEE
15 years 11 months ago
Towards Scalable Representations of Object Categories: Learning a Hierarchy of Parts
This paper proposes a novel approach to constructing a hierarchical representation of visual input that aims to enable recognition and detection of a large number of object catego...
Sanja Fidler, Ales Leonardis
PAMI
2006
117views more  PAMI 2006»
14 years 9 months ago
Metric Learning for Text Documents
High dimensional structured data such as text and images is often poorly understood and misrepresented in statistical modeling. The standard histogram representation suffers from ...
Guy Lebanon
ICCV
2011
IEEE
13 years 9 months ago
Domain Adaptation for Object Recognition: An Unsupervised Approach
Adapting the classifier trained on a source domain to recognize instances from a new target domain is an important problem that is receiving recent attention. In this paper, we p...
Raghuraman Gopalan, Ruonan Li, Rama Chellappa