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» ML-KNN: A lazy learning approach to multi-label learning
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ML
2000
ACM
154views Machine Learning» more  ML 2000»
13 years 6 months ago
Lazy Learning of Bayesian Rules
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
Zijian Zheng, Geoffrey I. Webb
TKDE
2010
168views more  TKDE 2010»
13 years 4 months ago
Completely Lazy Learning
—Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample. However, such methods are generally not complet...
Eric K. Garcia, Sergey Feldman, Maya R. Gupta, San...
CAV
2010
Springer
176views Hardware» more  CAV 2010»
13 years 8 months ago
Lazy Annotation for Program Testing and Verification
Abstract. We describe an interpolant-based approach to test generation and model checking for sequential programs. The method generates Floyd/Hoare style annotations of the program...
Kenneth L. McMillan
AIR
2005
119views more  AIR 2005»
13 years 6 months ago
An Assessment of Case-Based Reasoning for Spam Filtering
Because of the changing nature of spam, a spam filtering system that uses machine learning will need to be dynamic. This suggests that a case-based (memory-based) approach may work...
Sarah Jane Delany, Padraig Cunningham, Lorcan Coyl...
DAC
2006
ACM
14 years 7 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