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» Algorithms for Large, Sparse Network Alignment Problems
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120
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ML
2006
ACM
110views Machine Learning» more  ML 2006»
15 years 2 months ago
Classification-based objective functions
Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
Michael Rimer, Tony Martinez
223
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GIS
2007
ACM
16 years 3 months ago
Evacuation route planning: scalable heuristics
Given a transportation network, a vulnerable population, and a set of destinations, evacuation route planning identifies routes to minimize the time to evacuate the vulnerable pop...
Sangho Kim, Betsy George, Shashi Shekhar
122
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AUSAI
2005
Springer
15 years 8 months ago
Global Versus Local Constructive Function Approximation for On-Line Reinforcement Learning
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
Peter Vamplew, Robert Ollington
120
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BMCBI
2008
164views more  BMCBI 2008»
15 years 2 months ago
Word correlation matrices for protein sequence analysis and remote homology detection
Background: Classification of protein sequences is a central problem in computational biology. Currently, among computational methods discriminative kernel-based approaches provid...
Thomas Lingner, Peter Meinicke
114
Voted
ICASSP
2007
IEEE
15 years 9 months ago
Evolutionary Sequence Modeling for Discovery of Peptide Hormones
There are currently a large number of ‘‘orphan’’ G-protein-coupled receptors (GPCRs) whose endogenous ligands (peptide hormones) are unknown. Identification of these pepti...
M. Kemal Sönmez, Lawrence Toll, Nina Zaveri