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» Improving the lazy Krivine machine
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LISP
2007
74views more  LISP 2007»
14 years 9 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
15 years 10 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
15 years 10 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
15 years 2 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
14 years 10 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