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» Learning with Few Examples by Transferring Feature Relevance
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ICMCS
2007
IEEE
133views Multimedia» more  ICMCS 2007»
15 years 3 months ago
Data Modeling Strategies for Imbalanced Learning in Visual Search
In this paper we examine a novel approach to the difficult problem of querying video databases using visual topics with few examples. Typically with visual topics, the examples a...
Jelena Tesic, Apostol Natsev, Lexing Xie, John R. ...
CVPR
2005
IEEE
15 years 11 months ago
Object Recognition with Features Inspired by Visual Cortex
We introduce a novel set of features for robust object recognition. Each element of this set is a complex feature obtained by combining position- and scale-tolerant edgedetectors ...
Thomas Serre, Lior Wolf, Tomaso Poggio
SIGGRAPH
2010
ACM
15 years 2 months ago
Learning behavior styles with inverse reinforcement learning
We present a method for inferring the behavior styles of character controllers from a small set of examples. We show that a rich set of behavior variations can be captured by dete...
Seong Jae Lee, Zoran Popovic
FUIN
2010
268views more  FUIN 2010»
14 years 4 months ago
Boruta - A System for Feature Selection
Machine learning methods are often used to classify objects described by hundreds of attributes; in many applications of this kind a great fraction of attributes may be totally irr...
Miron B. Kursa, Aleksander Jankowski, Witold R. Ru...
IJON
2007
88views more  IJON 2007»
14 years 9 months ago
Information maximization in face processing
This perspective paper explores principles of unsupervised learning and how they relate to face recognition. Dependency coding and information maximization appear to be central pr...
Marian Stewart Bartlett