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» Sampling Methods for Unsupervised Learning
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CVPR
2001
IEEE
16 years 4 months ago
Small Sample Learning during Multimedia Retrieval using BiasMap
All positive examples are alike; each negative example is negative in its own way. During interactive multimedia information retrieval, the number of training samples fed-back by ...
Xiang Sean Zhou, Thomas S. Huang
ICML
2005
IEEE
16 years 3 months ago
Robust one-class clustering using hybrid global and local search
Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
Gunjan Gupta, Joydeep Ghosh
CVPR
2008
IEEE
16 years 4 months ago
Unsupervised estimation of segmentation quality using nonnegative factorization
We propose an unsupervised method for evaluating image segmentation. Common methods are typically based on evaluating smoothness within segments and contrast between them, and the...
Roman Sandler, Michael Lindenbaum
ICCAD
2008
IEEE
107views Hardware» more  ICCAD 2008»
15 years 8 months ago
Importance sampled circuit learning ensembles for robust analog IC design
This paper presents ISCLEs, a novel and robust analog design method that promises to scale with Moore’s Law, by doing boosting-style importance sampling on digital-sized circuit...
Peng Gao, Trent McConaghy, Georges G. E. Gielen
ESWA
2011
220views Database» more  ESWA 2011»
14 years 5 months ago
Unsupervised neural models for country and political risk analysis
This interdisciplinary research project focuses on relevant applications of Knowledge Discovery and Artificial Neural Networks in order to identify and analyse levels of country, b...
Álvaro Herrero, Emilio Corchado, Alfredo Ji...