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JMLR
2011
187views more  JMLR 2011»
13 years 2 months ago
Robust Statistics for Describing Causality in Multivariate Time Series
A widely agreed upon definition of time series causality inference, established in the seminal 1969 article of Clive Granger (1969), is based on the relative ability of the histor...
Florin Popescu
DASFAA
2008
IEEE
190views Database» more  DASFAA 2008»
14 years 1 months ago
Analysis of Time Series Using Compact Model-Based Descriptions
Abstract. Recently, we have proposed a novel method for the compression of time series based on mathematical models that explore dependencies between different time series. This r...
Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...
ICML
2005
IEEE
14 years 8 months ago
Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Xiaojin Zhu, John D. Lafferty
KDD
2009
ACM
364views Data Mining» more  KDD 2009»
14 years 8 months ago
Causality quantification and its applications: structuring and modeling of multivariate time series
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
Takashi Shibuya, Tatsuya Harada, Yasuo Kuniyoshi
KDD
2008
ACM
159views Data Mining» more  KDD 2008»
14 years 7 months ago
Semi-supervised learning with data calibration for long-term time series forecasting
Many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one ...
Haibin Cheng, Pang-Ning Tan