Online Forecasting Matrix Factorization

IEEE Transactions on Signal Processing(2019)

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摘要
We consider the problem of forecasting a high-dimensional time series that can be modeled as matrices where each column denotes a measurement and use low-rank matrix factorization for predicting future values or imputing missing ones. We define and analyze our problem in the online setting in which the data arrive as a stream and only a single pass is allowed. We present and analyze new matrix fac...
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关键词
Time series analysis,Forecasting,Matrix decomposition,Sparse matrices,Predictive models,State-space methods,Kalman filters
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