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VLDB
2006
ACM
162views Database» more  VLDB 2006»
15 years 11 months ago
Dependency trees in sub-linear time and bounded memory
We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...
Dan Pelleg, Andrew W. Moore
ALT
2010
Springer
15 years 22 days ago
Lower Bounds on Learning Random Structures with Statistical Queries
We show that random DNF formulas, random log-depth decision trees and random deterministic finite acceptors cannot be weakly learned with a polynomial number of statistical queries...
Dana Angluin, David Eisenstat, Leonid Kontorovich,...
ICML
1996
IEEE
16 years 2 hour ago
Learning Relational Concepts with Decision Trees
In this paper, we describe two di erent learning tasks for relational structures. When learning a classi er for structures, the relational structures in the training sets are clas...
Peter Geibel, Fritz Wysotzki
89
Voted
ICML
2002
IEEE
16 years 2 hour ago
Kernels for Semi-Structured Data
Semi-structured data such as XML and HTML is attracting considerable attention. It is important to develop various kinds of data mining techniques that can handle semistructured d...
Hisashi Kashima, Teruo Koyanagi
108
Voted
MLCW
2005
Springer
15 years 4 months ago
Textual Entailment Recognition Based on Dependency Analysis and WordNet
The Recognizing Textual Entailment System shown here is based on the use of a broad-coverage parser to extract dependency relationships; in addition, WordNet relations are used to ...
Jesús Herrera, Anselmo Peñas, Felisa...