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» Reformulating Constraint Models Using Input Data
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AUTOMATICA
2006
150views more  AUTOMATICA 2006»
14 years 9 months ago
Enlarging the terminal region of nonlinear model predictive control using the support vector machine method
In this paper, Receding Horizon Model Predictive Control (RHMPC) of nonlinear systems subject to input and state constraints is considered. We propose to estimate the terminal reg...
Chong Jin Ong, Dan Sui, Elmer G. Gilbert
ICONIP
2009
14 years 7 months ago
Learning Gaussian Process Models from Uncertain Data
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
CP
2007
Springer
15 years 1 months ago
Exploring Different Constraint-Based Modelings for Program Verification
Recently, constraint-programming techniques have been used to generate test data and to verify the conformity of a program with its specification. Constraint generated for these ta...
Hélène Collavizza, Michel Rueher
87
Voted
SSPR
2004
Springer
15 years 3 months ago
Tracking the Evolution of a Tennis Match Using Hidden Markov Models
The creation of a cognitive perception systems capable of inferring higher-level semantic information from low-level feature and event information for a given type of multimedia co...
Ilias Kolonias, William J. Christmas, Josef Kittle...
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
15 years 10 months ago
Transforming data to satisfy privacy constraints
Data on individuals and entities are being collected widely. These data can contain information that explicitly identifies the individual (e.g., social security number). Data can ...
Vijay S. Iyengar