Learning Theory and Algorithms for Forecasting Non-stationary Time Series

By Vitaly Kuznetsov, Mehryar Mohri. 2015

89 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Mehryar Mohri
2. Steven C. H. Hoi
3. Ananda Theertha Suresh
4. Yishay Mansour
5. Doyen Sahoo
6. Corinna Cortes
7. Chenghao Liu
8. Gerald Woo

Citations in the corpus

• A Theory of Multiple-Source Adaptation with Limited Target Labeled Data (2020, background): “A finer notion of discrepancy, which we will refer to as the label-discrepancy, was introduced by Mohri and Muñoz Medina (2012) (see also (Kuznetsov and Mohri, 2015)), which is useful in contexts where some target labeled data is available, as in our problem here.”
• ETSformer: Exponential Smoothing Transformers for Time-series Forecasting (2022, background): “(1) Firstly, time-series data is usually assumed to be generated by a conditional distribution over past observations, with the dependence between observations weakening over time [17, 23].”