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» Parameterized Learning Complexity
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FOCS
2005
IEEE
16 years 8 days ago
Mechanism Design via Machine Learning
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a wide variety of r...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
AMR
2005
Springer
117views Multimedia» more  AMR 2005»
16 years 6 days ago
Learning User Queries in Multimodal Dissimilarity Spaces
Abstract. Different strategies to learn user semantic queries from dissimilarity representations of video audio-visual content are presented. When dealing with large corpora of vi...
Eric Bruno, Nicolas Moënne-Loccoz, Sté...
CP
2004
Springer
16 years 2 days ago
Leveraging the Learning Power of Examples in Automated Constraint Acquisition
Constraint programming is rapidly becoming the technology of choice for modeling and solving complex combinatorial problems. However, users of constraint programming technology nee...
Christian Bessière, Remi Coletta, Eugene C....
COLT
2003
Springer
15 years 12 months ago
On Learning to Coordinate: Random Bits Help, Insightful Normal Forms, and Competency Isomorphisms
A mere bounded number of random bits judiciously employed by a probabilistically correct algorithmic coordinator is shown to increase the power of learning to coordinate compared ...
John Case, Sanjay Jain, Franco Montagna, Giulia Si...
NEUROSCIENCE
2001
Springer
15 years 11 months ago
Modularity and Specialized Learning: Mapping between Agent Architectures and Brain Organization
This volume is intended to help advance the field of artificial neural networks along the lines of complexity present in animal brains. In particular, we are interested in examin...
Joanna Bryson, Lynn Andrea Stein