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High-dimensional time series prediction is needed in applications as diverse as demand forecasting and climatology.
A new approach to linear filtering and prediction problems
Rudolph Emil Kalman · 1960
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An approach to time series smoothing and forecasting using the EM algorithm
Robert H. Shumway and David S. Stoffer · 1982
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Concrete Mathematics: A Foundation for Computer Science
Ronald L. Graham, Donald E. Knuth, and Oren Patashnik · 1994
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Parameter estimation for linear dynamical systems
Zoubin Ghahramani and Geoffrey E. Hinton · 1996
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Postwar us business cycles: an empirical investigation
Robert J. Hodrick and Edward C. Prescott · 1997
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Alexander J. Smola and Risi Kondor · 2003
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Nonnegative matrix factorization with temporal smoothness and/or spatial decorrelation constraints
Zhe Chen and Andrzej Cichocki · 2005
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Hansheng Wang, Guodong Li, and Chih-Ling Tsai · 2007
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\ \backslash ell_1 trend filtering
Seung-Jean Kim, Kwangmoo Koh, Stephen Boyd, and Dimitry Gorinevsky · 2009
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Matrix factorization techniques for recommender systems
Yehuda Koren, Robert M. Bell, and Chris Volinsky · 2009
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Liang Xiong, Xi Chen, Tzu-Kuo Huang, Jeff G Schneider, and Jaime G. Carbonell · 2010
Transition matrix estimation in high dimensional time series
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Provable inductive matrix completion
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Bayesian Forecasting and Dynamic Models
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Speedup matrix completion with side information: Application to multi-label learning
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Structured regularization for large vector autoregressions
William B. Nicholson, David S. Matteson, and Jacob Bien · 2014
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Parallel matrix factorization for recommender systems
Hsiang-Fu Yu, Cho-Jui Hsieh, Si Si, and Inderjit S. Dhillon · 2014
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