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» Learning with Few Examples by Transferring Feature Relevance
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COCOON
2005
Springer
15 years 3 months ago
A Quadratic Lower Bound for Rocchio's Similarity-Based Relevance Feedback Algorithm
Rocchio’s similarity-based relevance feedback algorithm, one of the most important query reformation methods in information retrieval, is essentially an adaptive supervised lear...
Zhixiang Chen, Bin Fu
CORR
2002
Springer
99views Education» more  CORR 2002»
14 years 9 months ago
The Identification of Context-Sensitive Features: A Formal Definition of Context for Concept Learning
A large body of research in machine learning is concerned with supervised learning from examples. The examples are typically represented as vectors in a multi-dimensional feature ...
Peter D. Turney
70
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MLDM
1999
Springer
15 years 1 months ago
Independent Feature Analysis for Image Retrieval
Content-based image retrieval methods based on the Euclidean metric expect the feature space to be isotropic. They su€er from unequal di€erential relevance of features in comput...
Jing Peng, Bir Bhanu
NIPS
2003
14 years 11 months ago
Learning a Rare Event Detection Cascade by Direct Feature Selection
Face detection is a canonical example of a rare event detection problem, in which target patterns occur with much lower frequency than nontargets. Out of millions of face-sized wi...
Jianxin Wu, James M. Rehg, Matthew D. Mullin
ICML
2006
IEEE
15 years 10 months ago
Active sampling for detecting irrelevant features
The general approach for automatically driving data collection using information from previously acquired data is called active learning. Traditional active learning addresses the...
Sriharsha Veeramachaneni, Emanuele Olivetti, Paolo...