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ICML
2007
IEEE
16 years 3 months ago
Multiclass multiple kernel learning
In many applications it is desirable to learn from several kernels. "Multiple kernel learning" (MKL) allows the practitioner to optimize over linear combinations of kern...
Alexander Zien, Cheng Soon Ong
IJCAI
2007
15 years 3 months ago
Reinforcement Learning of Local Shape in the Game of Go
We explore an application to the game of Go of a reinforcement learning approach based on a linear evaluation function and large numbers of binary features. This strategy has prov...
David Silver, Richard S. Sutton, Martin Mülle...
ICML
2008
IEEE
16 years 3 months ago
Localized multiple kernel learning
Recently, instead of selecting a single kernel, multiple kernel learning (MKL) has been proposed which uses a convex combination of kernels, where the weight of each kernel is opt...
Ethem Alpaydin, Mehmet Gönen
ICPR
2002
IEEE
16 years 3 months ago
Incorporating Conditional Independence Assumption with Support Vector Machines to Enhance Handwritten Character Segmentation Per
Learning Bayesian Belief Networks (BBN) from corpora and incorporating the extracted inferring knowledge with a Support Vector Machines (SVM) classifier has been applied to charac...
Manolis Maragoudakis, Ergina Kavallieratou, Nikos ...
HYBRID
2000
Springer
15 years 6 months ago
A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham