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» Dynamic Factor Graphs for Time Series Modeling
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ICASSP
2011
IEEE
12 years 9 months ago
Sparse graphical modeling of piecewise-stationary time series
Graphical models are useful for capturing interdependencies of statistical variables in various fields. Estimating parameters describing sparse graphical models of stationary mul...
Daniele Angelosante, Georgios B. Giannakis
ICDM
2006
IEEE
137views Data Mining» more  ICDM 2006»
13 years 11 months ago
Mining Complex Time-Series Data by Learning Markovian Models
In this paper, we propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of ...
Yi Wang, Lizhu Zhou, Jianhua Feng, Jianyong Wang, ...
ICML
2004
IEEE
14 years 6 months ago
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...
CSDA
2006
191views more  CSDA 2006»
13 years 5 months ago
Forecasting daily time series using periodic unobserved components time series models
We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend, seasonal and irregu...
Siem Jan Koopman, Marius Ooms
KDD
2010
ACM
263views Data Mining» more  KDD 2010»
13 years 9 months ago
Social action tracking via noise tolerant time-varying factor graphs
Users’ behaviors (actions) in a social network are influenced by various factors such as personal interests, social influence, and global trends. However, few publications sys...
Chenhao Tan, Jie Tang, Jimeng Sun, Quan Lin, Fengj...