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NC
2006
132views Neural Networks» more  NC 2006»
13 years 8 months ago
Learning short multivariate time series models through evolutionary and sparse matrix computation
Multivariate Time Series (MTS) data are widely available in different fields including medicine, finance, bioinformatics, science and engineering. Modelling MTS data accurately is...
Stephen Swift, Joost N. Kok, Xiaohui Liu
RSP
2005
IEEE
131views Control Systems» more  RSP 2005»
14 years 2 months ago
Models for Embedded Application Mapping onto NoCs: Timing Analysis
Networks-on-chip (NoCs) are an emergent communication infrastructure, which can be designed to deal with growing system complexity and technology evolution. The efficient use of N...
César A. M. Marcon, Márcio Eduardo K...
BMCBI
2007
215views more  BMCBI 2007»
13 years 8 months ago
Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregres
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
Rainer Opgen-Rhein, Korbinian Strimmer
CVPR
2009
IEEE
15 years 4 months ago
Locally Time-Invariant models of Human Activities using Trajectories on the Grassmanian
Human activity analysis is an important problem in computer vision with applications in surveillance and summarization and indexing of consumer content. Complex human activities...
Pavan Turaga, Rama Chellappa
ECRTS
2008
IEEE
14 years 3 months ago
A Gravitational Task Model for Target Sensitive Real-Time Applications
The commonly used task models for real-time systems focus on execution windows expressing earliest start times and deadlines of tasks for feasibility. Within these windows, execut...
Raphael Guerra, Gerhard Fohler