Fast algorithms for projected clustering
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
A direct approach to conformational dynamics based on hybrid Monte Carlo
Journal of Computational Physics - Special issue on computational molecular biophysics
Understanding Molecular Simulation: From Algorithms to Applications
Understanding Molecular Simulation: From Algorithms to Applications
Visualizing dynamic molecular conformations
Proceedings of the conference on Visualization '02
Local Dimensionality Reduction: A New Approach to Indexing High Dimensional Spaces
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Correlation analysis of spatial time series datasets: a filter-and-refine approach
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
Finite Element Approach to Clustering of Multidimensional Time Series
SIAM Journal on Scientific Computing
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We present a method for simultaneous dimension reduction and metastability analysis of high dimensional time series. The approach is based on the combination of hidden Markov models (HMMs) and principal component analysis. We derive optimal estimators for the log-likelihood functional and employ the Expectation Maximization algorithm for its numerical optimization. We demonstrate the performance of the method on a generic 102-dimensional example, apply the new HMM-PCA algorithm to a molecular dynamics simulation of 12–alanine in water and interpret the results.