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» Evaluating algorithms that learn from data streams
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ICML
2006
IEEE
16 years 7 months ago
Constructing informative priors using transfer learning
Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...
Rajat Raina, Andrew Y. Ng, Daphne Koller
IPPS
2008
IEEE
16 years 1 months ago
A dynamic scheduling approach for coordinated wide-area data transfers using GridFTP
Many scientific applications need to stage large volumes of files from one set of machines to another set of machines in a wide-area network. Efficient execution of such data t...
Gaurav Khanna 0002, Ümit V. Çataly&uum...
ICDAR
2003
IEEE
16 years 1 days ago
Evaluating SEE - A Benchmarking System for Document Page Segmentation
The decomposition of a document into segments such as text regions and graphics is a significant part of the document analysis process. The basic requirement for rating and impro...
Stefan Agne, Andreas Dengel, Bertin Klein
RECOMB
2006
Springer
16 years 7 months ago
Improving Prediction of Zinc Binding Sites by Modeling the Linkage Between Residues Close in Sequence
Abstract. We describe and empirically evaluate machine learning methods for the prediction of zinc binding sites from protein sequences. We start by observing that a data set consi...
Sauro Menchetti, Andrea Passerini, Paolo Frasconi,...
EVOW
2005
Springer
16 years 8 days ago
On the Application of Evolutionary Algorithms to the Consensus Tree Problem
Computing consensus trees amounts to finding a single tree that summarizes a collection of trees. Three evolutionary algorithms are defined for this problem, featuring characteri...
Carlos Cotta