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» Sampling Methods for Unsupervised Learning
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123
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MMM
2009
Springer
186views Multimedia» more  MMM 2009»
15 years 9 months ago
A New Multiple Kernel Approach for Visual Concept Learning
In this paper, we present a novel multiple kernel method to learn the optimal classification function for visual concept. Although many carefully designed kernels have been propose...
Jingjing Yang, Yuanning Li, YongHong Tian, Lingyu ...
ICB
2009
Springer
159views Biometrics» more  ICB 2009»
15 years 9 months ago
Multilinear Tensor-Based Non-parametric Dimension Reduction for Gait Recognition
The small sample size problem and the difficulty in determining the optimal reduced dimension limit the application of subspace learning methods in the gait recognition domain. To...
Changyou Chen, Junping Zhang, Rudolf Fleischer
106
Voted
ICCV
2011
IEEE
14 years 2 months ago
Source Constrained Clustering
We consider the problem of quantizing data generated from disparate sources, e.g. subjects performing actions with different styles, movies with particular genre bias, various con...
Ekaterina Taralova, Fernando DelaTorre, Martial He...
107
Voted
HUC
2003
Springer
15 years 8 months ago
Inferring High-Level Behavior from Low-Level Sensors
Abstract. We present a method of learning a Bayesian model of a traveler moving through an urban environment. This technique is novel in that it simultaneously learns a unified mo...
Donald J. Patterson, Lin Liao, Dieter Fox, Henry A...
93
Voted
HCI
2007
15 years 4 months ago
OntoGen: Semi-automatic Ontology Editor
In this paper we present a semi-automatic ontology editor as implemented in a new version of OntoGen system. The system integrates machine learning and text mining algorithms into ...
Blaz Fortuna, Marko Grobelnik, Dunja Mladenic