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» Incremental Parametric Development of Greedy Algorithms
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ENTCS
2007
121views more  ENTCS 2007»
13 years 4 months ago
Incremental Parametric Development of Greedy Algorithms
The event B method provides a general framework for modelling both data structures and algorithms. B models are validated by discharging proof obligations ensuring safety properti...
Dominique Cansell, Dominique Méry
JMLR
2002
106views more  JMLR 2002»
13 years 4 months ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
TNN
2010
159views Management» more  TNN 2010»
12 years 11 months ago
Multiple incremental decremental learning of support vector machines
We propose a multiple incremental decremental algorithm of Support Vector Machine (SVM). Conventional single incremental decremental SVM can update the trained model efficiently w...
Masayuki Karasuyama, Ichiro Takeuchi
CP
1999
Springer
13 years 9 months ago
An Interval Constraint Approach to Handle Parametric Ordinary Differential Equations for Decision Support
The behaviour of many systems is naturally modelled by a set of ordinary differential equations (ODEs) which are parametric. Since decisions are often based on relations over these...
Jorge Cruz, Pedro Barahona
SIAMSC
2010
159views more  SIAMSC 2010»
13 years 3 months ago
Parameter and State Model Reduction for Large-Scale Statistical Inverse Problems
A greedy algorithm for the construction of a reduced model with reduction in both parameter and state is developed for efficient solution of statistical inverse problems governed b...
Chad Lieberman, Karen Willcox, Omar Ghattas