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» Geometric Clustering Using the Information Bottleneck Method
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BMCBI
2007
146views more  BMCBI 2007»
14 years 9 months ago
Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data
Background: Transcriptional modules (TM) consist of groups of co-regulated genes and transcription factors (TF) regulating their expression. Two high-throughput (HT) experimental ...
Xiangdong Liu, Walter J. Jessen, Siva Sivaganesan,...
IDA
2007
Springer
14 years 9 months ago
Removing biases in unsupervised learning of sequential patterns
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
Yoav Horman, Gal A. Kaminka
158
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ICRA
2008
IEEE
471views Robotics» more  ICRA 2008»
15 years 4 months ago
Autonomous image-based exploration for mobile robot navigation
— Image-based navigation paradigms have recently emerged as an interesting alternative to conventional modelbased methods in mobile robotics. In this paper, we augment the existi...
D. Santosh, Supreeth Achar, C. V. Jawahar
IJCV
2002
185views more  IJCV 2002»
14 years 9 months ago
Vision and the Atmosphere
Current vision systems are designed to perform in clear weather. Needless to say, in any outdoor application, there is no escape from "bad" weather. Ultimately, computer ...
Srinivasa G. Narasimhan, Shree K. Nayar
RECOMB
2000
Springer
15 years 1 months ago
Contig selection in physical mapping
In physical mapping, one orders a set of genetic landmarks or a library of cloned fragments of DNA according to their position in the genome. Our approach to physical mapping divi...
Steffen Heber, Jens Stoye, Jörg D. Hoheisel, ...