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IDA
2002
Springer
14 years 9 months ago
Evolutionary model selection in unsupervised learning
Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and pos...
YongSeog Kim, W. Nick Street, Filippo Menczer
98
Voted
BMCBI
2006
139views more  BMCBI 2006»
14 years 9 months ago
Improvement in accuracy of multiple sequence alignment using novel group-to-group sequence alignment algorithm with piecewise li
Background: Multiple sequence alignment (MSA) is a useful tool in bioinformatics. Although many MSA algorithms have been developed, there is still room for improvement in accuracy...
Shinsuke Yamada, Osamu Gotoh, Hayato Yamana
INFOCOM
2010
IEEE
14 years 8 months ago
Worst-Case TCAM Rule Expansion
—Designers of TCAMs (ternary CAMs) for packet classification often have to deal with unpredictable sets of rules. These result in highly variable rule expansions, and can only r...
Ori Rottenstreich, Isaac Keslassy
ICRA
2010
IEEE
153views Robotics» more  ICRA 2010»
14 years 8 months ago
Learning to navigate through crowded environments
— The goal of this research is to enable mobile robots to navigate through crowded environments such as indoor shopping malls, airports, or downtown side walks. The key research ...
Peter Henry, Christian Vollmer, Brian Ferris, Diet...
NN
2010
Springer
125views Neural Networks» more  NN 2010»
14 years 8 months ago
Parameter-exploring policy gradients
We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in paramet...
Frank Sehnke, Christian Osendorfer, Thomas Rü...