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» Improving the lazy Krivine machine
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LISP
2007
74views more  LISP 2007»
13 years 5 months ago
Improving the lazy Krivine machine
Krivine presents the K machine, which produces weak head normal form results. Sestoft introduces several call-by-need variants of the K machine that implement result sharing via pu...
Daniel P. Friedman, Abdulaziz Ghuloum, Jeremy G. S...
ICML
2003
IEEE
14 years 6 months ago
Boosting Lazy Decision Trees
This paper explores the problem of how to construct lazy decision tree ensembles. We present and empirically evaluate a relevancebased boosting-style algorithm that builds a lazy ...
Xiaoli Zhang Fern, Carla E. Brodley
ICML
1999
IEEE
14 years 6 months ago
Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees
Lbr is a lazy semi-naive Bayesian classi er learning technique, designed to alleviate the attribute interdependence problem of naive Bayesian classi cation. To classify a test exa...
Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting
IPPS
2003
IEEE
13 years 10 months ago
Lazy Parallelization: A Finite State Machine Based Optimization Approach for Data Parallel Image Processing Applications
Performance obtained with existing library-based parallelization tools for implementing high performance image processing applications is often sub-optimal. This is because inter-...
Frank J. Seinstra, Dennis Koelma
OSDI
1996
ACM
13 years 6 months ago
Lazy Receiver Processing (LRP): A Network Subsystem Architecture for Server Systems
The explosive growth of the Internet, the widespread use of WWW-related applications, and the increased reliance on client-server architectures places interesting new demands on n...
Peter Druschel, Gaurav Banga