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» On regularization algorithms in learning theory
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MOBIHOC
2012
ACM
13 years 7 months ago
Spatial spectrum access game: nash equilibria and distributed learning
A key feature of wireless communications is the spatial reuse. However, the spatial aspect is not yet well understood for the purpose of designing efficient spectrum sharing mecha...
Xu Chen, Jianwei Huang
169
Voted
STOC
2012
ACM
196views Algorithms» more  STOC 2012»
13 years 7 months ago
Time-space tradeoffs in resolution: superpolynomial lower bounds for superlinear space
We give the first time-space tradeoff lower bounds for Resolution proofs that apply to superlinear space. In particular, we show that there are formulas of size N that have Reso...
Paul Beame, Christopher Beck, Russell Impagliazzo
152
Voted
GECCO
2007
Springer
213views Optimization» more  GECCO 2007»
15 years 10 months ago
Genetically programmed learning classifier system description and results
An agent population can be evolved in a complex environment to perform various tasks and optimize its job performance using Learning Classifier System (LCS) technology. Due to the...
Gregory Anthony Harrison, Eric W. Worden
FOCS
1990
IEEE
15 years 8 months ago
Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Avrim Blum
JMLR
2010
163views more  JMLR 2010»
14 years 11 months ago
Dense Message Passing for Sparse Principal Component Analysis
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
Kevin Sharp, Magnus Rattray