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AAAI
2008
13 years 10 months ago
Ensemble Forecasting for Disease Outbreak Detection
We describe a method to improve detection of disease outbreaks in pre-diagnostic time series data. The method uses multiple forecasters and learns the linear combination to minimi...
Thomas H. Lotze, Galit Shmueli
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
13 years 11 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
IWANN
2005
Springer
14 years 1 months ago
Input and Structure Selection for k-NN Approximator
Abstract. This paper presents k-NN as an approximator for time series prediction problems. The main advantage of this approximator is its simplicity. Despite the simplicity, k-NN c...
Antti Sorjamaa, Nima Reyhani, Amaury Lendasse
PKDD
2010
Springer
184views Data Mining» more  PKDD 2010»
13 years 6 months ago
Shift-Invariant Grouped Multi-task Learning for Gaussian Processes
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
Yuyang Wang, Roni Khardon, Pavlos Protopapas
SIGGRAPH
1996
ACM
13 years 11 months ago
A Volumetric Method for Building Complex Models from Range Images
A number of techniques have been developed for reconstructing surfaces by integrating groups of aligned range images. A desirable set of properties for such algorithms includes: i...
Brian Curless, Marc Levoy