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» Random Sampling of States in Dynamic Programming
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IJAIT
2000
142views more  IJAIT 2000»
13 years 7 months ago
Adequacy of Limited Testing for Knowledge Based Systems
Knowledge-based engineering and computational intelligence are expected to become core technologies in the design and manufacturing for the next generation of space exploration mi...
Tim Menzies, Bojan Cukic
ICML
2000
IEEE
14 years 1 days ago
A Bayesian Framework for Reinforcement Learning
The reinforcement learning problem can be decomposed into two parallel types of inference: (i) estimating the parameters of a model for the underlying process; (ii) determining be...
Malcolm J. A. Strens
BMCBI
2007
148views more  BMCBI 2007»
13 years 7 months ago
Computation of significance scores of unweighted Gene Set Enrichment Analyses
Background: Gene Set Enrichment Analysis (GSEA) is a computational method for the statistical evaluation of sorted lists of genes or proteins. Originally GSEA was developed for in...
Andreas Keller, Christina Backes, Hans-Peter Lenho...
ICML
2003
IEEE
14 years 8 months ago
Marginalized Kernels Between Labeled Graphs
A new kernel function between two labeled graphs is presented. Feature vectors are defined as the counts of label paths produced by random walks on graphs. The kernel computation ...
Hisashi Kashima, Koji Tsuda, Akihiro Inokuchi
IPSN
2004
Springer
14 years 1 months ago
Estimation from lossy sensor data: jump linear modeling and Kalman filtering
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal