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JAIR
2000
152views more  JAIR 2000»
13 years 9 months ago
Value-Function Approximations for Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Milos Hauskrecht
BMCBI
2006
72views more  BMCBI 2006»
13 years 9 months ago
Selecting effective siRNA sequences by using radial basis function network and decision tree learning
Background: Although short interfering RNA (siRNA) has been widely used for studying gene functions in mammalian cells, its gene silencing efficacy varies markedly and there are o...
Shigeru Takasaki, Yoshihiro Kawamura, Akihiko Kona...
CORR
2006
Springer
109views Education» more  CORR 2006»
13 years 9 months ago
Decision Making with Side Information and Unbounded Loss Functions
We consider the problem of decision-making with side information and unbounded loss functions. Inspired by probably approximately correct learning model, we use a slightly differe...
Majid Fozunbal, Ton Kalker
ICCS
2007
Springer
14 years 1 months ago
Efficient Measurement of the Eye Blinking by Using Decision Function for Intelligent Vehicles
In this paper, we propose an efficient measurement of the eye blinking for drowsy driver detection system that is one of the driver safety systems for the intelligent vehicle. Howe...
Ilkwon Park, Jung-Ho Ahn, Hyeran Byun
INCDM
2010
Springer
138views Data Mining» more  INCDM 2010»
13 years 8 months ago
Learning Discriminative Distance Functions for Case Retrieval and Decision Support
The importance of learning distance functions is gradually being acknowledged by the machine learning community, and different techniques are suggested that can successfully learn ...
Alexey Tsymbal, Martin Huber, Shaohua Kevin Zhou