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» Transfer Learning in Decision Trees
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IJCAI
2003
13 years 9 months ago
Inductive Learning in Less Than One Sequential Data Scan
Most recent research of scalable inductive learning on very large dataset, decision tree construction in particular, focuses on eliminating memory constraints and reducing the num...
Wei Fan, Haixun Wang, Philip S. Yu, Shaw-hwa Lo
ACL
1997
13 years 9 months ago
Learning Features that Predict Cue Usage
Our goal is to identify the features that predict the occurrence and placement of discourse cues in tutorial explanations in order to aid in the automatic generation of explanatio...
Barbara Di Eugenio, Johanna D. Moore, Massimo Paol...
SEMWEB
2007
Springer
14 years 1 months ago
Learning Subsumption Relations with CSR: a Classification based Method for the Alignment of Ontologies
In this paper we propose the "Classification-Based Learning of Subsumption Relations for the Alignment of Ontologies" (CSR) method. Given a pair of concepts from two onto...
Vassilis Spiliopoulos, Alexandros G. Valarakos, Ge...
ICIP
2005
IEEE
14 years 9 months ago
Learning to binarize document images using a decision cascade
In this article, we propose a special type of decision tree, called a decision cascade, for binarizing document images. Such images are produced by cameras, resulting in varying de...
Chien-Hsing Chou, Chih-Ching Huang, Wen-Hsiung Lin...
ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
13 years 6 months ago
Generalized model learning for Reinforcement Learning on a humanoid robot
— Reinforcement learning (RL) algorithms have long been promising methods for enabling an autonomous robot to improve its behavior on sequential decision-making tasks. The obviou...
Todd Hester, Michael Quinlan, Peter Stone