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» A Training Method with Small Computation for Classification
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SIGUCCS
2003
ACM
14 years 1 months ago
Student staff: n. an energetic, brilliant, creative, talented potential rolled into a food-driven, sleep-deprived, unmotivated c
Students are a wonderful resource for any department of a college or university, especially an ITS department. They are inexpensive and abundant. They want to work at strange time...
Karen McRitchie
CHI
2004
ACM
14 years 8 months ago
Single-handed interaction techniques for multiple pressure-sensitive strips
We present a set of interaction techniques that make novel use of a small pressure-sensitive pad to allow one-handed direct control of a large number of parameters. The surface of...
Gábor Blaskó, Steven Feiner
ECCV
2006
Springer
14 years 9 months ago
Extending Kernel Fisher Discriminant Analysis with the Weighted Pairwise Chernoff Criterion
Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...
Guang Dai, Dit-Yan Yeung, Hong Chang
ECCV
2010
Springer
13 years 8 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
ECCV
2006
Springer
14 years 9 months ago
Sampling Representative Examples for Dimensionality Reduction and Recognition - Bootstrap Bumping LDA
Abstract. We present a novel method for dimensionality reduction and recognition based on Linear Discriminant Analysis (LDA), which specifically deals with the Small Sample Size (S...
Hui Gao, James W. Davis