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AAAI
1996
13 years 6 months ago
Learning Efficient Rules by Maintaining the Explanation Structure
Many learning systems suffer from the utility problem; that is, that time after learning is greater than time before learning. Discovering how to assure that learned knowledge wil...
Jihie Kim, Paul S. Rosenbloom
ICML
2000
IEEE
14 years 5 months ago
A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets
This paper has no novel learning or statistics: it is concerned with making a wide class of preexisting statistics and learning algorithms computationally tractable when faced wit...
Paul Komarek, Andrew W. Moore
TEC
2010
126views more  TEC 2010»
12 years 11 months ago
Learning the Large-Scale Structure of the MAX-SAT Landscape Using Populations
A new algorithm for solving MAX-SAT problems is introduced which clusters good solutions, and restarts the search from the closest feasible solution to the centroid of each cluster...
Mohamed Qasem, Adam Prügel-Bennett
ICAI
2010
13 years 3 months ago
An Efficient Sequential Covering Algorithm for Explaining Subsets of Data
Given a subset of data that differs from the rest, a user often wants an explanation as to why this is the case. For instance, in a database of flights, a user may want to understa...
Matthew Michelson, Sofus A. Macskassy
VLDB
1991
ACM
81views Database» more  VLDB 1991»
13 years 8 months ago
On Maintaining Priorities in a Production Rule System
We present a priority system which is particularly suited for production rules coupled to databases. In this system, there are default priorities between all rules and overriding ...
Rakesh Agrawal, Roberta Cochrane, Bruce G. Lindsay