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199
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KDD
2009
ACM
364views Data Mining» more  KDD 2009»
16 years 7 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
NIPS
2001
15 years 8 months ago
Bayesian time series classification
This paper proposes an approach to classification of adjacent segments of a time series as being either of classes. We use a hierarchical model that consists of a feature extract...
Peter Sykacek, Stephen J. Roberts
177
Voted
MICCAI
2004
Springer
16 years 7 months ago
Solving Incrementally the Fitting and Detection Problems in fMRI Time Series
We tackle the problem of real-time statistical analysis of functional magnetic resonance imaging (fMRI) data. In a recent paper, we proposed an incremental algorithm based on the e...
Alexis Roche, Philippe Pinel, Stanislas Dehaene, J...
223
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MMDB
2004
ACM
153views Multimedia» more  MMDB 2004»
16 years 2 days ago
A PCA-based similarity measure for multivariate time series
Multivariate time series (MTS) datasets are common in various multimedia, medical and financial applications. We propose a similarity measure for MTS datasets, Eros (Extended Fro...
Kiyoung Yang, Cyrus Shahabi
ICIP
2010
IEEE
15 years 4 months ago
Sparse shapes prototype modeling using genetic algorithms
The process of finding representative shape patterns from sparse datasets is a challenging task: especially for non-rigid objects, shape deformations through time can produce very...
Stefano Maludrottu, Hany Sallam, Carlo S. Regazzon...