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EMNLP
2007
15 years 8 months ago
Bootstrapping Feature-Rich Dependency Parsers with Entropic Priors
One may need to build a statistical parser for a new language, using only a very small labeled treebank together with raw text. We argue that bootstrapping a parser is most promis...
David A. Smith, Jason Eisner
BMCBI
2008
131views more  BMCBI 2008»
15 years 6 months ago
K-OPLS package: Kernel-based orthogonal projections to latent structures for prediction and interpretation in feature space
Background: Kernel-based classification and regression methods have been successfully applied to modelling a wide variety of biological data. The Kernel-based Orthogonal Projectio...
Max Bylesjö, Mattias Rantalainen, Jeremy K. N...
VAMOS
2010
Springer
15 years 4 months ago
The Variability Model of The Linux Kernel
Lack of realistic benchmarks hinders efficient design and evaluation of analysis techniques for feature models. We extract a variability model from the code base of the Linux kerne...
Steven She, Rafael Lotufo, Thorsten Berger, Andrze...
DCC
2006
IEEE
16 years 6 months ago
Compression and Machine Learning: A New Perspective on Feature Space Vectors
The use of compression algorithms in machine learning tasks such as clustering and classification has appeared in a variety of fields, sometimes with the promise of reducing probl...
D. Sculley, Carla E. Brodley
MEDINFO
2007
15 years 7 months ago
An Ontology-based Model of Clinical Information
In this paper we describe a model of clinical information designed to make health information systems properly interoperable and safely computable. The model is a response to a nu...
Thomas Beale, Sam Heard