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KDD
2009
ACM
364views Data Mining» more  KDD 2009»
14 years 5 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
13 years 6 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
MICCAI
2004
Springer
14 years 5 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...
MMDB
2004
ACM
153views Multimedia» more  MMDB 2004»
13 years 10 months 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
13 years 2 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...