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MCS
2005
Springer
15 years 9 months ago
Ensembles of Classifiers from Spatially Disjoint Data
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
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ICML
2009
IEEE
16 years 5 months ago
Unsupervised search-based structured prediction
We describe an adaptation and application of a search-based structured prediction algorithm "Searn" to unsupervised learning problems. We show that it is possible to red...
Hal Daumé III
GRAPHITE
2003
ACM
15 years 9 months ago
Applying game design theory to virtual heritage environments
Much literature has argued that interactive engagement in a computer medium is best demonstrated by games. With this in mind, this paper suggests certain techniques that virtual e...
Erik Champion
NEUROSCIENCE
2001
Springer
15 years 8 months ago
Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Doina Caragea, Adrian Silvescu, Vasant Honavar
ICML
2007
IEEE
16 years 5 months ago
On the relation between multi-instance learning and semi-supervised learning
Multi-instance learning and semi-supervised learning are different branches of machine learning. The former attempts to learn from a training set consists of labeled bags each con...
Zhi-Hua Zhou, Jun-Ming Xu