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» Parameterized Learning Complexity
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JFR
2006
108views more  JFR 2006»
15 years 6 months ago
Learning in a hierarchical control system: 4D/RCS in the DARPA LAGR program
The Defense Applied Research Projects Agency (DARPA) Learning Applied to Ground Vehicles (LAGR) program aims to develop algorithms for autonomous vehicle navigation that learn how...
James S. Albus, Roger Bostelman, Tommy Chang, Tsai...
CVPR
2008
IEEE
16 years 8 months ago
Learning and using taxonomies for fast visual categorization
The computational complexity of current visual categorization algorithms scales linearly at best with the number of categories. The goal of classifying simultaneously Ncat = 104 -...
Gregory Griffin, Darya Perona
ICFCA
2005
Springer
15 years 12 months ago
Lessons Learned in Applying Formal Concept Analysis to Reverse Engineering
A key difficulty in the maintenance and evolution of complex software systems is to recognize and understand the implicit dependencies that define contracts that must be respecte...
Gabriela Arévalo, Stéphane Ducasse, ...
GECCO
2003
Springer
112views Optimization» more  GECCO 2003»
15 years 11 months ago
Multi-agent Learning of Heterogeneous Robots by Evolutionary Subsumption
Abstract. Many multi-robot systems are heterogeneous cooperative systems, systems consisting of different species of robots cooperating with each other to achieve a common goal. T...
Hongwei Liu, Hitoshi Iba
HAIS
2009
Springer
15 years 10 months ago
Beyond Homemade Artificial Data Sets
One of the most important challenges in supervised learning is how to evaluate the quality of the models evolved by different machine learning techniques. Up to now, we have relied...
Núria Macià, Albert Orriols-Puig, Es...