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» The Stochastic Machine Replenishment Problem
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NIPS
2001
13 years 11 months ago
Online Learning with Kernels
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
IEEEARES
2009
IEEE
14 years 4 months ago
A Framework for Understanding Botnets
Botnets have become a severe threat to the cyberspace. However, existing studies are typically conducted in an ad hoc fashion, by demonstrating specific analysis on captured bot ...
Justin Leonard, Shouhuai Xu, Ravi S. Sandhu
JAIR
2010
131views more  JAIR 2010»
13 years 8 months ago
Automatic Induction of Bellman-Error Features for Probabilistic Planning
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
Jia-Hong Wu, Robert Givan
ECML
1993
Springer
14 years 1 months ago
Complexity Dimensions and Learnability
In machine learning theory, problem classes are distinguished because of di erences in complexity. In 6 , a stochastic model of learning from examples was introduced. This PAClear...
Shan-Hwei Nienhuys-Cheng, Mark Polman
ICML
2004
IEEE
14 years 10 months ago
Utile distinction hidden Markov models
This paper addresses the problem of constructing good action selection policies for agents acting in partially observable environments, a class of problems generally known as Part...
Daan Wierstra, Marco Wiering