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We consider the problem of forecasting multiple values of the future of a vector time series, using some past values.
The approximation of one matrix by another of lower rank
Carl Eckart and Gale Young · 1936
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Norbert Wiener · 1950
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Alan Izenman · 1975
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John Geweke · 1977
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Michel Verhaegen · 1991
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Peter Van Overschee and Bart De Moor · 1992
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Michel Verhaegen · 1993
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Peter Van Overschee and Bart De Moor · 1994
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Jerome Connor, Douglas Martin, and Les Atlas · 1994
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Zhuanxin Ding and Clive W. J. Granger · 1996
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Ian Goodfellow, Yoshua Bengio, and Aaron Courville · 2016
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