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» Algorithms for Large, Sparse Network Alignment Problems
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144
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ML
2006
ACM
110views Machine Learning» more  ML 2006»
15 years 4 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
GIS
2007
ACM
16 years 6 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
AUSAI
2005
Springer
15 years 10 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
138
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BMCBI
2008
164views more  BMCBI 2008»
15 years 5 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
ICASSP
2007
IEEE
15 years 11 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