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» On Bayesian model and variable selection using MCMC
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KDD
2009
ACM
230views Data Mining» more  KDD 2009»
15 years 2 months ago
Grouped graphical Granger modeling methods for temporal causal modeling
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
AUTONOMICS
2009
ACM
15 years 4 months ago
Sensor Selection for IT Infrastructure Monitoring
Supervisory control is the main means to assure a high level performance and availability of large IT infrastructures. Applied control theory is used in physical and virtualization...
Gergely János Paljak, Imre Kocsis, Zolt&aac...
TEC
2008
118views more  TEC 2008»
14 years 9 months ago
RM-MEDA: A Regularity Model-Based Multiobjective Estimation of Distribution Algorithm
Under mild conditions, it can be induced from the Karush-Kuhn-Tucker condition that the Pareto set, in the decision space, of a continuous multiobjective optimization problem is (m...
Qingfu Zhang, Aimin Zhou, Yaochu Jin
ICASSP
2007
IEEE
15 years 4 months ago
A Multi-Subject, Dynamic Bayesian Networks (DBNS) Framework for Brain Effective Connectivity
As dynamic connectivity is shown essential for normal brain function and is disrupted in disease, it is critical to develop models for inferring brain effective connectivity from ...
Junning Li, Z. Jane Wang, Martin J. McKeown
BMCBI
2007
128views more  BMCBI 2007»
14 years 9 months ago
Model order selection for bio-molecular data clustering
Background: Cluster analysis has been widely applied for investigating structure in bio-molecular data. A drawback of most clustering algorithms is that they cannot automatically ...
Alberto Bertoni, Giorgio Valentini