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BMCBI
2007
172views more  BMCBI 2007»
13 years 11 months ago
Bayesian approaches to reverse engineer cellular systems: a simulation study on nonlinear Gaussian networks
Background: Reverse engineering cellular networks is currently one of the most challenging problems in systems biology. Dynamic Bayesian networks (DBNs) seem to be particularly su...
Fulvia Ferrazzi, Paola Sebastiani, Marco Ramoni, R...
INFOCOM
2005
IEEE
14 years 4 months ago
Connection admission control for flow level QoS in bufferless models
Abstract— Admission control algorithms used in access networks for multiplexed voice sources are typically based on aggregated system characteristics, such as aggregate loss prob...
Sándor Rácz, Tamás Jakabfy, J...
TIT
2008
100views more  TIT 2008»
13 years 10 months ago
Communication Via Decentralized Processing
Abstract-- The common problem of a nomadic terminal sending information to a remote destination via agents with lossless connections is investigated. Such a setting suits, e.g. acc...
Amichai Sanderovich, Shlomo Shamai, Yossef Steinbe...
ICML
2003
IEEE
14 years 11 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty

Book
778views
15 years 9 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...