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» Learning Rules from Distributed Data
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128
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RSEISP
2007
Springer
15 years 8 months ago
Generalizing Data in Natural Language
This paper concerns the development of a new direction in machine learning, called natural induction, which requires from computergenerated knowledge not only to have high predicti...
Ryszard S. Michalski, Janusz Wojtusiak
CLEF
2006
Springer
15 years 6 months ago
Experimenting a "General Purpose" Textual Entailment Learner in AVE
In this paper we present the use of a "general purpose" textual entaiment recognizer in the Answer Validation Exercise (AVE) task. Our system has been developed to learn...
Fabio Massimo Zanzotto, Alessandro Moschitti
ADMA
2006
Springer
110views Data Mining» more  ADMA 2006»
15 years 6 months ago
Learning with Local Drift Detection
Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Gladys Castillo
157
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JMLR
2006
186views more  JMLR 2006»
15 years 2 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani
KDD
1997
ACM
184views Data Mining» more  KDD 1997»
15 years 6 months ago
JAM: Java Agents for Meta-Learning over Distributed Databases
In this paper, we describe the JAM system, a distributed, scalable and portable agent-based data mining system that employs a general approach to scaling data mining applications ...
Salvatore J. Stolfo, Andreas L. Prodromidis, Shell...