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» Learning Instance-Specific Predictive Models
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ICPP
2006
IEEE
14 years 2 months ago
Performance Modeling based on Multidimensional Surface Learning for Performance Predictions of Parallel Applications in Non-Dedi
Modeling the performance behavior of parallel applications to predict the execution times of the applications for larger problem sizes and number of processors has been an active ...
Jay Yagnik, H. A. Sanjay, Sathish S. Vadhiyar
ICANN
2009
Springer
14 years 3 months ago
Adaptive Ensemble Models of Extreme Learning Machines for Time Series Prediction
Abstract. In this paper, we investigate the application of adaptive ensemble models of Extreme Learning Machines (ELMs) to the problem of one-step ahead prediction in (non)stationa...
Mark van Heeswijk, Yoan Miche, Tiina Lindh-Knuutil...
SGAI
2007
Springer
14 years 2 months ago
Learning Sets of Sub-Models for Spatio-Temporal Prediction
In this paper we describe a novel technique which implements a spatiotemporal model as a set of sub-models based on first order logic. These sub-models model different, typicall...
Andrew Bennett, Derek R. Magee
RECOMB
2009
Springer
14 years 9 months ago
Learning Models for Aligning Protein Sequences with Predicted Secondary Structure
Accurately aligning distant protein sequences is notoriously difficult. A recent approach to improving alignment accuracy is to use additional information such as predicted seconda...
Eagu Kim, Travis J. Wheeler, John D. Kececioglu
ALT
1998
Springer
14 years 26 days ago
Predictive Learning Models for Concept Drift
Concept drift means that the concept about which data is obtained may shift from time to time, each time after some minimum permanence. Except for this minimum permanence, the con...
John Case, Sanjay Jain, Susanne Kaufmann, Arun Sha...