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JMLR
2011
187views more  JMLR 2011»
14 years 6 months ago
Robust Statistics for Describing Causality in Multivariate Time Series
A widely agreed upon definition of time series causality inference, established in the seminal 1969 article of Clive Granger (1969), is based on the relative ability of the histor...
Florin Popescu
SADM
2010
141views more  SADM 2010»
14 years 6 months ago
A parametric mixture model for clustering multivariate binary data
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
Ajit C. Tamhane, Dingxi Qiu, Bruce E. Ankenman
VISSYM
2004
15 years 1 months ago
A Botanically Inspired High-Dimensional Visualization with Multivariate Glyphs
It is difficult for the average viewer to assimilate and comprehend huge amounts of high-dimensional data. It is important to present data in a way that allows the user a high lev...
Eleanor Boyle Chlan, Penny Rheingans
IDA
2003
Springer
15 years 5 months ago
Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies
Abstract. Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any mode...
Allan Tucker, Xiaohui Liu
ATAL
2007
Springer
15 years 5 months ago
Robust coordination to sustain throughput of an unstable agent network
We present a multi-agent coordination technique to maintain throughput of a large-scale agent network system in the face of failures of agents. Failures do not just deteriorate th...
Rajesh Gautam, Kazuo Miyashita