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» Evaluating algorithms that learn from data streams
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CIKM
2008
Springer
15 years 8 months ago
Metric-based ontology learning
Ontology learning is an important task in Artificial Intelligence, Semantic Web and Text Mining. This paper presents a novel framework for, and solutions to, three practical probl...
Hui Yang, Jamie Callan
ICDM
2009
IEEE
97views Data Mining» more  ICDM 2009»
16 years 1 months ago
Hierarchical Probabilistic Segmentation of Discrete Events
—Segmentation, the task of splitting a long sequence of discrete symbols into chunks, can provide important information about the nature of the sequence that is understandable to...
Guy Shani, Christopher Meek, Asela Gunawardana
EH
2003
IEEE
90views Hardware» more  EH 2003»
15 years 12 months ago
Evolving Sinusoidal Oscillators Using Genetic Algorithms
In the present paper, single-opamp sinusoidal oscillators are synthesized using genetic algorithms. The motivation is to evolve new topologies of oscillators using different activ...
Varun Aggarwal
PAKDD
2005
ACM
132views Data Mining» more  PAKDD 2005»
16 years 5 days ago
SETRED: Self-training with Editing
Self-training is a semi-supervised learning algorithm in which a learner keeps on labeling unlabeled examples and retraining itself on an enlarged labeled training set. Since the s...
Ming Li, Zhi-Hua Zhou
CORR
2010
Springer
151views Education» more  CORR 2010»
15 years 6 months ago
The Challenge of Believability in Video Games: Definitions, Agents Models and Imitation Learning
In this paper, we address the problem of creating believable agents (virtual characters) in video games. We consider only one meaning of believability, "giving the feeling of...
Fabien Tencé, Cédric Buche, Pierre D...