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AIMDM
1999
Springer
13 years 9 months ago
Knowledge-Based Event Detection in Complex Time Series Data
This paper describes an approach to the detection of events in complex, multi-channel, high frequency data. The example used is that of detecting the re-siting of a transcutaneous ...
Jim Hunter, Neil McIntosh
CEC
2009
IEEE
13 years 11 months ago
Evolving hypernetwork models of binary time series for forecasting price movements on stock markets
— The paper proposes a hypernetwork-based method for stock market prediction through a binary time series problem. Hypernetworks are a random hypergraph structure of higher-order...
Elena Bautu, Sun Kim, Andrei Bautu, Henri Luchian,...
ICML
2009
IEEE
14 years 5 months ago
Detecting the direction of causal time series
We propose a method that detects the true direction of time series, by fitting an autoregressive moving average model to the data. Whenever the noise is independent of the previou...
Arthur Gretton, Bernhard Schölkopf, Dominik J...
ICASSP
2011
IEEE
12 years 8 months ago
Multiple-channel detection of a Gaussian time series over frequency-flat channels
This work addresses the problem of deciding whether a set of realizations of a vector-valued time series with unknown temporal correlation are spatially correlated or not. Speciï¬...
David Ramírez, Javier Vía, Ignacio S...
KDD
2000
ACM
115views Data Mining» more  KDD 2000»
13 years 8 months ago
Mining asynchronous periodic patterns in time series data
Periodicy detection in time series data is a challenging problem of great importance in many applications. Most previous work focused on mining synchronous periodic patterns and d...
Jiong Yang, Wei Wang 0010, Philip S. Yu