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MLDM
2007
Springer
15 years 10 months ago
Transductive Learning from Relational Data
Transduction is an inference mechanism “from particular to particular”. Its application to classification tasks implies the use of both labeled (training) data and unlabeled (...
Michelangelo Ceci, Annalisa Appice, Nicola Barile,...
KDD
2012
ACM
207views Data Mining» more  KDD 2012»
13 years 7 months ago
Robust multi-task feature learning
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
Pinghua Gong, Jieping Ye, Changshui Zhang
AGENTS
1997
Springer
15 years 8 months ago
Modeling Motivations and Emotions as a Basis for Intelligent Behavior
We report on an experiment to implement an autonomous creature situated in a two-dimensional world, that shows various learning and problem-solving capabilities, within the Societ...
Dolores Cañamero
ESANN
2004
15 years 6 months ago
Data Mining Techniques on the Evaluation of Wireless Churn
This work focuses on one of the most critical issues to plague the wireless telecommunications industry today: the loss of a valuable subscriber to a competitor, also defined as ch...
Jorge Ferreira, Marley B. R. Vellasco, Marco Aur&e...
142
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EMNLP
2010
15 years 2 months ago
What a Parser Can Learn from a Semantic Role Labeler and Vice Versa
In many NLP systems, there is a unidirectional flow of information in which a parser supplies input to a semantic role labeler. In this paper, we build a system that allows inform...
Stephen A. Boxwell, Dennis Mehay, Chris Brew