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CVPR
2010
IEEE
15 years 1 days ago
Robust RVM regression using sparse outlier model
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
IJAIT
2008
99views more  IJAIT 2008»
14 years 12 months ago
Optimal Basic Block Instruction Scheduling for Multiple-Issue Processors Using Constraint Programming
Instruction scheduling is one of the most important steps for improving the performance of object code produced by a compiler. A fundamental problem that arises in instruction sch...
Abid M. Malik, Jim McInnes, Peter van Beek
WSC
2007
15 years 2 months ago
Parallel cross-entropy optimization
The Cross-Entropy (CE) method is a modern and effective optimization method well suited to parallel implementations. There is a vast array of problems today, some of which are hig...
Gareth E. Evans, Jonathan M. Keith, Dirk P. Kroese
EUROGP
2006
Springer
138views Optimization» more  EUROGP 2006»
15 years 3 months ago
Evolving Crossover Operators for Function Optimization
Abstract. A new model for evolving crossover operators for evolutionary function optimization is proposed in this paper. The model is a hybrid technique that combines a Genetic Pro...
Laura Diosan, Mihai Oltean
PE
2010
Springer
102views Optimization» more  PE 2010»
14 years 10 months ago
Extracting state-based performance metrics using asynchronous iterative techniques
Solution of large sparse linear fixed-point problems lies at the heart of many important performance analysis calculations. These calculations include steady-state, transient and...
Douglas V. de Jager, Jeremy T. Bradley