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» Learning with Few Examples by Transferring Feature Relevance
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ICML
2007
IEEE
14 years 5 months ago
Learning a meta-level prior for feature relevance from multiple related tasks
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
CVPR
2004
IEEE
14 years 6 months ago
Learning Object Detection from a Small Number of Examples: The Importance of Good Features
Face detection systems have recently achieved high detection rates[11, 8, 5] and real-time performance[11]. However, these methods usually rely on a huge training database (around...
Kobi Levi, Yair Weiss
ECCC
2006
96views more  ECCC 2006»
13 years 4 months ago
When Does Greedy Learning of Relevant Features Succeed? --- A Fourier-based Characterization ---
Detecting the relevant attributes of an unknown target concept is an important and well studied problem in algorithmic learning. Simple greedy strategies have been proposed that s...
Jan Arpe, Rüdiger Reischuk
PAMI
1998
113views more  PAMI 1998»
13 years 4 months ago
Example-Based Learning for View-Based Human Face Detection
—We present an example-based learning approach for locating vertical frontal views of human faces in complex scenes. The technique models the distribution of human face patterns ...
Kah Kay Sung, Tomaso Poggio
ICIAP
1999
ACM
13 years 9 months ago
Learning Visual Operators from Examples: A New Paradigm in Image Processing
This paper presents a general strategy for designing efficient visual operators. The approach is highly task oriented and what constitutes the relevant information is defined by...
Hans Knutsson, Magnus Borga