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157
Voted
ML
2008
ACM
222views Machine Learning» more  ML 2008»
15 years 3 months ago
Boosted Bayesian network classifiers
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg
162
Voted
ICALT
2010
IEEE
15 years 2 months ago
Reusing Adaptation Strategies in Adaptive Educational Hypermedia Systems
—Due to the difficulty and thus effort and expenses involved in creating them, personalization strategies in learning environments have to demonstrate a higher returnon-investmen...
Joshua Scotton, Alexandra I. Cristea
140
Voted
ML
2008
ACM
15 years 3 months ago
Incremental exemplar learning schemes for classification on embedded devices
Although memory-based classifiers offer robust classification performance, their widespread usage on embedded devices is hindered due to the device's limited memory resources...
Ankur Jain, Daniel Nikovski
149
Voted
JIRS
2000
144views more  JIRS 2000»
15 years 3 months ago
An Integrated Approach of Learning, Planning, and Execution
Agents (hardware or software) that act autonomously in an environment have to be able to integrate three basic behaviors: planning, execution, and learning. This integration is man...
Ramón García-Martínez, Daniel...
156
Voted
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 4 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy