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ICDM
2005
IEEE
189views Data Mining» more  ICDM 2005»
15 years 3 months ago
Integrating Hidden Markov Models and Spectral Analysis for Sensory Time Series Clustering
We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to da...
Jie Yin, Qiang Yang
IWANN
2005
Springer
15 years 3 months ago
Input Selection for Long-Term Prediction of Time Series
Prediction of time series is an important problem in many areas of science and engineering. Extending the horizon of predictions further to the future is the challenging and diffic...
Jarkko Tikka, Jaakko Hollmén, Amaury Lendas...
86
Voted
COMPGEOM
1997
ACM
15 years 1 months ago
Time-Series Similarity Problems and Well-Separated Geometric Sets
Given a pair of nonidentical complex objects, de ning and determining how similar they are to each other is a nontrivial problem. In data mining applications, one frequently nee...
Béla Bollobás, Gautam Das, Dimitrios...
80
Voted
NECO
1998
121views more  NECO 1998»
14 years 9 months ago
Nonlinear Time-Series Prediction with Missing and Noisy Data
We derive solutions for the problem of missing and noisy data in nonlinear timeseries prediction from a probabilistic point of view. We discuss different approximations to the so...
Volker Tresp, Reimar Hofmann
KDD
2008
ACM
159views Data Mining» more  KDD 2008»
15 years 10 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