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» Gaussian process for nonstationary time series prediction
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EDBT
2004
ACM
110views Database» more  EDBT 2004»
14 years 8 months ago
Using Convolution to Mine Obscure Periodic Patterns in One Pass
The mining of periodic patterns in time series databases is an interesting data mining problem that can be envisioned as a tool for forecasting and predicting the future behavior o...
Mohamed G. Elfeky, Walid G. Aref, Ahmed K. Elmagar...
ICASSP
2011
IEEE
13 years 10 days ago
An inner-product lower-bound estimate for dynamic time warping
In this paper, we present a lower-bound estimate for dynamic time warping (DTW) on time series consisting of multi-dimensional posterior probability vectors known as posteriorgram...
Yaodong Zhang, James R. Glass
KES
2010
Springer
13 years 7 months ago
Evolving takagi sugeno modelling with memory for slow processes
Evolving Takagi Sugeno (eTS) models are optimised for use in applications with high sampling rates. This mode of use produces excellent prediction results very quickly and with lo...
Simon McDonald, Plamen P. Angelov
PVLDB
2008
138views more  PVLDB 2008»
13 years 8 months ago
A skip-list approach for efficiently processing forecasting queries
Time series data is common in many settings including scientific and financial applications. In these applications, the amount of data is often very large. We seek to support pred...
Tingjian Ge, Stanley B. Zdonik
TITB
2010
123views Education» more  TITB 2010»
13 years 3 months ago
The pseudotemporal bootstrap for predicting glaucoma from cross-sectional visual field data
Progressive loss of the field of vision is characteristic of a number of eye diseases such as glaucoma, a leading cause of irreversible blindness in the world. Recently, there has ...
Allan Tucker, David Garway-Heath