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» A Theory for Memory-Based Learning
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COLT
2008
Springer
15 years 1 months ago
Learning from Collective Behavior
Inspired by longstanding lines of research in sociology and related fields, and by more recent largepopulation human subject experiments on the Internet and the Web, we initiate a...
Michael Kearns, Jennifer Wortman
ALT
2010
Springer
15 years 1 months ago
Bayesian Active Learning Using Arbitrary Binary Valued Queries
We explore a general Bayesian active learning setting, in which the learner can ask arbitrary yes/no questions. We derive upper and lower bounds on the expected number of queries r...
Liu Yang, Steve Hanneke, Jaime G. Carbonell
ILP
2000
Springer
15 years 3 months ago
Induction of Recursive Theories in the Normal ILP Setting: Issues and Solutions
Induction of recursive theories in the normal ILP setting is a complex task because of the non-monotonicity of the consistency property. In this paper we propose computational solu...
Floriana Esposito, Donato Malerba, Francesca A. Li...
CORR
2010
Springer
101views Education» more  CORR 2010»
14 years 11 months ago
Online Learning: Random Averages, Combinatorial Parameters, and Learnability
We develop a theory of online learning by defining several complexity measures. Among them are analogues of Rademacher complexity, covering numbers and fatshattering dimension fro...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
GECCO
2006
Springer
175views Optimization» more  GECCO 2006»
15 years 3 months ago
A computational theory of adaptive behavior based on an evolutionary reinforcement mechanism
Two mathematical and two computational theories from the field of human and animal learning are combined to produce a more general theory of adaptive behavior. The cornerstone of ...
J. J. McDowell, Paul L. Soto, Jesse Dallery, Saule...