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» On learning algorithm selection for classification
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133
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CVPR
2007
IEEE
16 years 4 months ago
Human Detection via Classification on Riemannian Manifolds
We present a new algorithm to detect humans in still images utilizing covariance matrices as object descriptors. Since these descriptors do not lie on a vector space, well known m...
Oncel Tuzel, Fatih Porikli, Peter Meer
104
Voted
ICML
2004
IEEE
16 years 3 months ago
Decentralized detection and classification using kernel methods
We consider the problem of decentralized detection under constraints on the number of bits that can be transmitted by each sensor. In contrast to most previous work, in which the ...
XuanLong Nguyen, Martin J. Wainwright, Michael I. ...
BMCBI
2007
153views more  BMCBI 2007»
15 years 2 months ago
Analysis of nanopore detector measurements using Machine-Learning methods, with application to single-molecule kinetic analysis
Background: A nanopore detector has a nanometer-scale trans-membrane channel across which a potential difference is established, resulting in an ionic current through the channel ...
Matthew Landry, Stephen Winters-Hilt
ICPR
2008
IEEE
15 years 9 months ago
Semi-supervised feature selection under logistic I-RELIEF framework
We consider feature selection in the semi-supervised learning setting. This problem is rarely addressed in the literature. We propose a new algorithm as a natural extension of the...
Yubo Cheng, Yunpeng Cai, Yijun Sun, Jian Li
ICML
2002
IEEE
16 years 3 months ago
Active + Semi-supervised Learning = Robust Multi-View Learning
In a multi-view problem, the features of the domain can be partitioned into disjoint subsets (views) that are sufficient to learn the target concept. Semi-supervised, multi-view a...
Ion Muslea, Steven Minton, Craig A. Knoblock