Abstract
We consider the problem of sequential prediction of arbitrary real-valued sequences with side information. We first construct a universal algorithm that asymptotically achieves the performance of the best side-information dependent constant predictor, uniformly for all data and side-information sequences. We then extend these results to linear predictors of some fixed order. We derive matching upper and lower bounds, and show that the algorithms are not only universal but they are also optimal such that no sequential algorithm can give better performance for all sequences.
| Original language | English (US) |
|---|---|
| Pages (from-to) | V-469-V-472 |
| Journal | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
| Volume | 5 |
| State | Published - 2004 |
| Event | Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing - Montreal, Que, Canada Duration: May 17 2004 → May 21 2004 |
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering