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» Evaluating algorithms that learn from data streams
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207
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JMLR
2012
13 years 9 months ago
Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets
We propose a new method for comparing learning algorithms on multiple tasks which is based on a novel non-parametric test that we call the Poisson binomial test. The key aspect of...
Alexandre Lacoste, François Laviolette, Mar...
199
Voted
CRV
2009
IEEE
115views Robotics» more  CRV 2009»
16 years 1 months ago
Learning Model Complexity in an Online Environment
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...
Dan Levi, Shimon Ullman
ISCIS
2005
Springer
16 years 15 days ago
Classification of Volatile Organic Compounds with Incremental SVMs and RBF Networks
Support Vector Machines (SVMs) have been applied to solve the classification of volatile organic compounds (VOC) data in some recent studies. SVMs provide good generalization perfo...
Zeki Erdem, Robi Polikar, Nejat Yumusak, Fikret S....
CSL
2002
Springer
15 years 6 months ago
Learning visually grounded words and syntax for a scene description task
A spoken language generation system has been developed that learns to describe objects in computer-generated visual scenes. The system is trained by a `show-and-tell' procedu...
Deb K. Roy
204
Voted
DILS
2005
Springer
16 years 16 days ago
Information Integration and Knowledge Acquisition from Semantically Heterogeneous Biological Data Sources
Abstract. We present INDUS (Intelligent Data Understanding System), a federated, query-centric system for knowledge acquisition from autonomous, distributed, semantically heterogen...
Doina Caragea, Jyotishman Pathak, Jie Bao, Adrian ...