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» The complexity of approximating entropy
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JMLR
2010
141views more  JMLR 2010»
15 years 22 days ago
Hierarchical Gaussian Process Regression
We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...
Sunho Park, Seungjin Choi
SOCO
2010
Springer
15 years 20 days ago
Using evolution strategies to solve DEC-POMDP problems
Decentralized partially observable Markov decision process (DEC-POMDP) is an approach to model multi-robot decision making problems under uncertainty. Since it is NEXP-complete the...
Baris Eker, H. Levent Akin
TCS
2010
15 years 20 days ago
A fluid analysis framework for a Markovian process algebra
Markovian process algebras, such as PEPA and stochastic -calculus, bring a powerful compositional approach to the performance modelling of complex systems. However, the models gen...
Richard A. Hayden, Jeremy T. Bradley
ISBI
2011
IEEE
14 years 9 months ago
Exact integration of diffusion orientation distribution functions for graph-based diffusion MRI analysis
Graph-based image analysis methods are increasingly being applied to diffusion MRI (dMRI) analysis. Unfortunately, weighting the graph for these methods involves solving a complex...
Brian G. Booth, Ghassan Hamarneh

Book
376views
17 years 3 months ago
An Exploration of Random Processes for Engineers
"From an applications viewpoint, the main reason to study the subject of these notes is to help deal with the complexity of describing random, time-varying functions. A random...
Bruce Hajek