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SDM
2007
SIAM
198views Data Mining» more  SDM 2007»
15 years 4 months ago
Learning from Time-Changing Data with Adaptive Windowing
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Albert Bifet, Ricard Gavaldà
ENTCS
2008
144views more  ENTCS 2008»
15 years 2 months ago
Platform Independent Timing of Java Virtual Machine Bytecode Instructions
The accurate measurement of the execution time of Java bytecode is one factor that is important in order to estimate the total execution time of a Java application running on a Ja...
Jonathan M. Lambert, James F. Power
IJCNN
2007
IEEE
15 years 9 months ago
Neural Network Ensembles for Time Series Prediction
— Rapidly evolving businesses generate massive amounts of time-stamped data sequences and defy a demand for massively multivariate time series analysis. For such data the predict...
Dymitr Ruta, Bogdan Gabrys

Book
361views
17 years 12 days ago
Introduction to Statistical Signal Processing
"A random or stochastic process is a mathematical model for a phenomenon that evolves in time in an unpredictable manner from the viewpoint of the observer. The phenomenon m...
R.M. Gray
FORMATS
2004
Springer
15 years 8 months ago
Lazy Approximation for Dense Real-Time Systems
We propose an effective and complete method for verifying safety and properties of timed systems, which is based on predicate abstraction for g finite abstractions of timed autom...
Maria Sorea