Model Agnostic Time Series Analysis via Matrix Estimation
<jats:p>We propose an algorithm to impute and forecast a time series by transforming the observed time series into a matrix, utilizing matrix estimation to recover missing values and de-noise observed entries, and performing linear regression to make predictions. At the core of our analysis is...
| Κύριοι συγγραφείς: | , , , |
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| Άλλοι συγγραφείς: | |
| Μορφή: | Άρθρο |
| Γλώσσα: | English |
| Έκδοση: |
Association for Computing Machinery (ACM)
2021
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| Διαθέσιμο Online: | https://hdl.handle.net/1721.1/135068 |