5.txt

This complete matlab for neural network

发信人: GzLi (笑梨), 信区: DataMining
标  题:  Machine Learning 47(2/3) <5>
发信站: 南京大学小百合站 (Thu Jul 18 00:45:40 2002), 站内信件
篇名： Theory Revision with Queries&colon; DNF Formulas 
刊名： Machine Learning 
ISSN： 0885-6125 
卷期： 47 卷 2/3 期 出版日期： 200205/06  
页码： 从 257 页到 295 页共 39 页 
作者： Goldsmith Judy   Department of Computer Science, University of Kentucky
, 763 Anderson Hall, Lexington, KY 40506, USA. [e-mail]
 
Sloan Robert H.   Department of Computer Science, University of Illinois 
at Chicago, and National Science Foundation. [e-mail]
 
Turán Gy?rgy   Math, Stat., & Computer Science Department, University of
 Illinois at Chicago, Research Group on AI of Hungarian Academy of Sciences
 at University of Szeged. [e-mail]
 
 
文摘： 
The theory revision, or concept revision, problem is to correct a given, 
roughly correct concept. This problem is considered here in the model of 
learning with equivalence and membership queries. A revision algorithm is
 considered efficient if the number of queries it makes is polynomial in 
the revision distance between the initial theory and the target theory, and
 polylogarithmic in the number of variables and the size of the initial theory
. The revision distance is the minimal number of syntactic revision operations
, such as the deletion or addition of literals, needed to obtain the target
 theory from the initial theory. Efficient revision algorithms are given 
for three classes of disjunctive normal form expressions&colon; monotone 
k-DNF, monotone m-term DNF and unate two-term DNF. A negative result shows
 that some monotone DNF formulas are hard to revise.
 


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