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» Near-optimal Observation Selection using Submodular Function...
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NIPS
2004
13 years 9 months ago
Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms
We provide a worst-case analysis of selective sampling algorithms for learning linear threshold functions. The algorithms considered in this paper are Perceptron-like algorithms, ...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
AIPS
2009
13 years 8 months ago
A Decision-Theoretic Approach to Dynamic Sensor Selection in Camera Networks
Nowadays many urban areas have been equipped with networks of surveillance cameras, which can be used for automatic localization and tracking of people. However, given the large r...
Matthijs T. J. Spaan, Pedro U. Lima
RECOMB
2000
Springer
13 years 11 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, ...
ICML
2003
IEEE
14 years 8 months ago
Margin Distribution and Learning
Recent theoretical results have shown that improved bounds on generalization error of classifiers can be obtained by explicitly taking the observed margin distribution of the trai...
Ashutosh Garg, Dan Roth
BMCBI
2006
165views more  BMCBI 2006»
13 years 7 months ago
Improving the quality of protein structure models by selecting from alignment alternatives
Background: In the area of protein structure prediction, recently a lot of effort has gone into the development of Model Quality Assessment Programs (MQAPs). MQAPs distinguish hig...
Ingolf Sommer, Stefano Toppo, Oliver Sander, Thoma...