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ICDCS
2000
IEEE
15 years 11 months ago
The Effect of Nogood Learning in Distributed Constraint Satisfaction
We present resolvent-based learning as a new nogood learning method for a distributed constraint satisfaction algorithm. This method is based on a look-back technique in constrain...
Makoto Yokoo, Katsutoshi Hirayama
ER
1999
Springer
146views Database» more  ER 1999»
15 years 11 months ago
"Modeling-by-Patterns" of Web Applications
“A pattern ... describes a problem which occurs over and over again in our environment, and then describes the core of the solution to that problem, in such a way that you can us...
Franca Garzotto, Paolo Paolini, Davide Bolchini, S...
VLDB
1997
ACM
142views Database» more  VLDB 1997»
15 years 11 months ago
Algorithms for Materialized View Design in Data Warehousing Environment
Selecting views to materialize is one of the most important decisions in designing a data warehouse. In this paper, we present a framework for analyzing the issues in selecting vi...
Jian Yang, Kamalakar Karlapalem, Qing Li
GECCO
2007
Springer
144views Optimization» more  GECCO 2007»
15 years 10 months ago
Mixing independent classifiers
In this study we deal with the mixing problem, which concerns combining the prediction of independently trained local models to form a global prediction. We deal with it from the ...
Jan Drugowitsch, Alwyn Barry
AMT
2006
Springer
147views Multimedia» more  AMT 2006»
15 years 10 months ago
Semi-Supervised Text Classification Using Positive and Unlabeled Data
Text classification using positive and unlabeled data refers to the problem of building text classifier using positive documents (P) of one class and unlabeled documents (U) of man...
Shuang Yu, Xueyuan Zhou, Chunping Li