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» Learning Business Process Models: A Case Study
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NIPS
2008
15 years 7 months ago
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
WSC
2000
15 years 7 months ago
Parallel execution of a sequential network simulator
Parallel discrete event simulation (PDES) techniques have not yet made a substantial impact on the network simulation community because of the need to recast the simulation models...
Kevin G. Jones, Samir Ranjan Das
227
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CISIS
2011
IEEE
14 years 6 months ago
Improving Scheduling Techniques in Heterogeneous Systems with Dynamic, On-Line Optimisations
—Computational performance increasingly depends on parallelism, and many systems rely on heterogeneous resources such as GPUs and FPGAs to accelerate computationally intensive ap...
Marcin Bogdanski, Peter R. Lewis, Tobias Becker, X...
CCE
2005
15 years 6 months ago
Integrating CDU, FCC and product blending models into refinery planning
The accuracy of using linear models for crude distillation unit (CDU), fluidize-bed catalytic cracker (FCC) and product blending in refinery planning has been debated for decades....
Wenkai Li, Chi-Wai Hui, AnXue Li
ICML
2009
IEEE
16 years 6 months ago
Detecting the direction of causal time series
We propose a method that detects the true direction of time series, by fitting an autoregressive moving average model to the data. Whenever the noise is independent of the previou...
Arthur Gretton, Bernhard Schölkopf, Dominik J...