Sciweavers

1989 search results - page 45 / 398
» Learning to Select Useful Landmarks
Sort
View
ICPR
2006
IEEE
14 years 10 months ago
On Kernel Selection in Relevance Vector Machines Using Stability Principle
In this paper we propose an alternative interpretation of Bayesian learning based on maximal evidence principle. We establish a notion of local evidence which can be viewed as a c...
Dmitry Kropotov, Nikita Ptashko, Oleg Vasiliev, Dm...
NAACL
2004
13 years 11 months ago
Ensemble-based Active Learning for Parse Selection
Supervised estimation methods are widely seen as being superior to semi and fully unsupervised methods. However, supervised methods crucially rely upon training sets that need to ...
Miles Osborne, Jason Baldridge
CIARP
2004
Springer
14 years 3 months ago
Unsupervised Learning of Ontology-Linked Selectional Preferences
We present a method for extracting selectional preferences of verbs from unannotated text. These selectional preferences are linked to an ontology (e.g. the hypernym relations foun...
Hiram Calvo, Alexander F. Gelbukh
DAC
2006
ACM
14 years 10 months ago
Predicate learning and selective theory deduction for a difference logic solver
Design and verification of systems at the Register-Transfer (RT) or behavioral level require the ability to reason at higher levels of abstraction. Difference logic consists of an...
Chao Wang, Aarti Gupta, Malay K. Ganai
CORR
2006
Springer
130views Education» more  CORR 2006»
13 years 9 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...