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CVPR
2007
IEEE
16 years 6 months ago
Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition
We present an unsupervised method for learning a hierarchy of sparse feature detectors that are invariant to small shifts and distortions. The resulting feature extractor consists...
Marc'Aurelio Ranzato, Fu Jie Huang, Y-Lan Boureau,...
CVPR
2007
IEEE
16 years 6 months ago
Hybrid learning of large jigsaws
A jigsaw is a recently proposed generative model that describes an image as a composition of non-overlapping patches of varying shape, extracted from a latent image. By learning t...
Julia A. Lasserre, Anitha Kannan, John M. Winn
CVPR
2008
IEEE
16 years 6 months ago
Joint tracking of features and edges
Sparse features have traditionally been tracked from frame to frame independently of one another. We propose a framework in which features are tracked jointly. Combining ideas fro...
Stanley T. Birchfield, Shrinivas J. Pundlik
ICML
2004
IEEE
16 years 5 months ago
The Bayesian backfitting relevance vector machine
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
KDD
2001
ACM
187views Data Mining» more  KDD 2001»
16 years 4 months ago
Random projection in dimensionality reduction: applications to image and text data
Random projections have recently emerged as a powerful method for dimensionality reduction. Theoretical results indicate that the method preserves distances quite nicely; however,...
Ella Bingham, Heikki Mannila