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» Unsupervised Feature Selection Using Feature Similarity
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DMIN
2009
185views Data Mining» more  DMIN 2009»
13 years 8 months ago
A Sparse Coding Based Similarity Measure
In high dimensional data sets not all dimensions contain an equal amount of information and most of the time global features are more important than local differences. This makes ...
Sebastian Klenk, Gunther Heidemann
ICANN
2005
Springer
14 years 3 months ago
Learning Features of Intermediate Complexity for the Recognition of Biological Motion
Humans can recognize biological motion from strongly impoverished stimuli, like point-light displays. Although the neural mechanism underlying this robust perceptual process have n...
Rodrigo Sigala, Thomas Serre, Tomaso Poggio, Marti...
ICDAR
2007
IEEE
14 years 4 months ago
A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images
We describe an unsupervised learning algorithm for extracting sparse and locally shift-invariant features. We also devise a principled procedure for learning hierarchies of invari...
Marc'Aurelio Ranzato, Yann LeCun
ICCBR
2007
Springer
14 years 4 months ago
Catching the Drift: Using Feature-Free Case-Based Reasoning for Spam Filtering
In this paper, we compare case-based spam filters, focusing on their resilience to concept drift. In particular, we evaluate how to track concept drift using a case-based spam fi...
Sarah Jane Delany, Derek G. Bridge
ICCV
2011
IEEE
12 years 10 months ago
Gradient-based learning of higher-order image features
Recent work on unsupervised feature learning has shown that learning on polynomial expansions of input patches, such as on pair-wise products of pixel intensities, can improve the...
Roland Memisevic