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HIS
2004
13 years 10 months ago
Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
COMMA
2008
13 years 10 months ago
Arguments from Experience: The PADUA Protocol
In this paper we describe PADUA, a protocol designed to enable agents to debate an issue drawing arguments not from a knowledge base of facts, rules and priorities but directly fro...
Maya Wardeh, Trevor J. M. Bench-Capon, Frans Coene...
JAIR
2006
110views more  JAIR 2006»
13 years 8 months ago
Domain Adaptation for Statistical Classifiers
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
Hal Daumé III, Daniel Marcu
CIKM
1997
Springer
14 years 24 days ago
A Framework for the Management of Past Experiences with Time-Extended Situations
: In the context of knowledge management, we focus on the representation and the retrieval of past experiences called cases within the Case-Based Reasoning (CBR) paradigm. CBR is a...
Michel Jaczynski
CE
2008
91views more  CE 2008»
13 years 8 months ago
Mining e-Learning domain concept map from academic articles
Recent researches have demonstrated the importance of concept map and its versatile applications especially in e-Learning. For example, while designing adaptive learning materials...
Nian-Shing Chen, Kinshuk, Chun-Wang Wei, Hong-Jhe ...