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PKDD
2009
Springer
155views Data Mining» more  PKDD 2009»
15 years 4 months ago
Dynamic Factor Graphs for Time Series Modeling
Abstract. This article presents a method for training Dynamic Factor Graphs (DFG) with continuous latent state variables. A DFG includes factors modeling joint probabilities betwee...
Piotr W. Mirowski, Yann LeCun
GECCO
2005
Springer
119views Optimization» more  GECCO 2005»
15 years 2 months ago
A new evolutionary method for time series forecasting
This paper presents a new method — the Time-delay Added Evolutionary Forecasting (TAEF) method — for time series prediction which performs an evolutionary search of the minimu...
Tiago A. E. Ferreira, Germano C. Vasconcelos, Paul...
SDM
2007
SIAM
171views Data Mining» more  SDM 2007»
14 years 10 months ago
A Better Alternative to Piecewise Linear Time Series Segmentation
Time series are difficult to monitor, summarize and predict. Segmentation organizes time series into few intervals having uniform characteristics (flatness, linearity, modality,...
Daniel Lemire
GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
14 years 10 months ago
A hybrid method for tuning neural network for time series forecasting
This paper presents an study about a new Hybrid method GRASPES - for time series prediction, inspired in F. Takens theorem and based on a multi-start metaheuristic for combinatori...
Aranildo Rodrigues Lima Junior, Tiago Alessandro E...
KDD
1998
ACM
190views Data Mining» more  KDD 1998»
15 years 1 months ago
Time Series Forecasting from High-Dimensional Data with Multiple Adaptive Layers
This paper describes our work in learning online models that forecast real-valued variables in a high-dimensional space. A 3GB database was collected by sampling 421 real-valued s...
R. Bharat Rao, Scott Rickard, Frans Coetzee