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» Unsupervised Learning in Spectral Genome Analysis
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FBIT
2007
IEEE
13 years 11 months ago
Unsupervised Learning in Spectral Genome Analysis
The tree representation as a model for organismal evolution has been in use since before Darwin. However, with the recent unprecedented access to biomolecular data it has been dis...
Lutz Hamel, Neha Nahar, Maria S. Poptsova, Olga Zh...
TIT
2008
224views more  TIT 2008»
13 years 4 months ago
Graph-Based Semi-Supervised Learning and Spectral Kernel Design
We consider a framework for semi-supervised learning using spectral decomposition-based unsupervised kernel design. We relate this approach to previously proposed semi-supervised l...
Rie Johnson, Tong Zhang
ENGL
2007
180views more  ENGL 2007»
13 years 4 months ago
Biological Data Mining for Genomic Clustering Using Unsupervised Neural Learning
— The paper aims at designing a scheme for automatic identification of a species from its genome sequence. A set of 64 three-tuple keywords is first generated using the four type...
Shreyas Sen, Seetharam Narasimhan, Amit Konar
ECML
2006
Springer
13 years 8 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
ICIP
2007
IEEE
14 years 6 months ago
Unsupervised Modeling of Object Tracks for Fast Anomaly Detection
A key goal of far-field activity analysis is to learn the usual pattern of activity in a scene and to detect statistically anomalous behavior. We propose a method for unsupervised...
Tomas Izo, W. Eric L. Grimson