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ECML
2007
Springer
14 years 2 months ago
Structure Learning of Probabilistic Relational Models from Incomplete Relational Data
Abstract. Existing relational learning approaches usually work on complete relational data, but real-world data are often incomplete. This paper proposes the MGDA approach to learn...
Xiao-Lin Li, Zhi-Hua Zhou
FOCS
2003
IEEE
14 years 1 months ago
Learning DNF from Random Walks
We consider a model of learning Boolean functions from examples generated by a uniform random walk on {0, 1}n . We give a polynomial time algorithm for learning decision trees and...
Nader H. Bshouty, Elchanan Mossel, Ryan O'Donnell,...
ECML
1993
Springer
14 years 2 days ago
SIA: A Supervised Inductive Algorithm with Genetic Search for Learning Attributes based Concepts
This paper describes a genetic learning system called SIA, which learns attributes based rules from a set of preclassified examples. Examples may be described with a variable numbe...
Gilles Venturini
KDD
2006
ACM
113views Data Mining» more  KDD 2006»
14 years 8 months ago
A new efficient probabilistic model for mining labeled ordered trees
Mining frequent patterns is a general and important issue in data mining. Complex and unstructured (or semi-structured) datasets have appeared in major data mining applications, i...
Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhi...
ISMB
1994
13 years 9 months ago
Predicting Location and Structure Of beta-Sheet Regions Using Stochastic Tree Grammars
We describe and demonstrate the effectiveness of a method of predicting protein secondary structures, sheet regions in particular, using a class of stochastic tree grammars as rep...
Hiroshi Mamitsuka, Naoki Abe