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» Learning the Common Structure of Data
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WSC
2007
13 years 9 months ago
Using empirical demand data and common random numbers in an agent-based simulation of a distribution network
Agent-based simulation provides a methodology to investigate complex systems behavior, such as supply chains, while incorporating many empirical elements relative to both systems ...
William J. Sawaya
JSS
2007
126views more  JSS 2007»
13 years 6 months ago
Fine-grain analysis of common coupling and its application to a Linux case study
Common coupling (sharing global variables across modules) is widely accepted as a measure of software quality and maintainability; a low level of common coupling is necessary (but...
Dror G. Feitelson, Tokunbo O. S. Adeshiyan, Daniel...
ML
2010
ACM
151views Machine Learning» more  ML 2010»
13 years 5 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
ICPR
2010
IEEE
13 years 10 months ago
Learning a Joint Manifold Representation from Multiple Data Sets
—The problem we address in the paper is how to learn a joint representation from data lying on multiple manifolds. We are given multiple data sets and there is an underlying comm...
Marwan Torki, Ahmed Elgammal, Chan-Su Lee
LREC
2008
140views Education» more  LREC 2008»
13 years 8 months ago
Toward Active Learning in Data Selection: Automatic Discovery of Language Features During Elicitation
Data Selection has emerged as a common issue in language technologies. We define Data Selection as the choosing of a subset of training data that is most effective for a given tas...
Jonathan Clark, Robert E. Frederking, Lori S. Levi...