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PAKDD
2009
ACM
151views Data Mining» more  PAKDD 2009»
14 years 3 months ago
Budget Semi-supervised Learning
In this paper we propose to study budget semi-supervised learning, i.e., semi-supervised learning with a resource budget, such as a limited memory insufficient to accommodate and/...
Zhi-Hua Zhou, Michael Ng, Qiao-Qiao She, Yuan Jian...
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
FLAIRS
2000
13 years 9 months ago
A Parallel Approach to Modeling Language Learning and Understanding in Young Children
To reduce the complexity of studying a parallel mechanism for natural language learning and understanding which supports both utterance and discourse processing, we propose a comp...
Charles Hannon, Diane J. Cook
ICML
2009
IEEE
14 years 9 months ago
Structure learning of Bayesian networks using constraints
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
Cassio Polpo de Campos, Zhi Zeng, Qiang Ji
ICML
2003
IEEE
14 years 9 months ago
Relational Instance Based Regression for Relational Reinforcement Learning
Relational reinforcement learning (RRL) is a Q-learning technique which uses first order regression techniques to generalize the Qfunction. Both the relational setting and the Q-l...
Kurt Driessens, Jan Ramon