Uniform error bounds for quantized dynamical models
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2026
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866917277981474816 |
|---|---|
| author | Metakalard, Abdelkader Lauer, Fabien Colin, Kevin Gilson, Marion |
| author_facet | Metakalard, Abdelkader Lauer, Fabien Colin, Kevin Gilson, Marion |
| contents | This paper provides statistical guarantees on the accuracy of dynamical models learned from dependent data sequences. Specifically, we develop uniform error bounds that apply to quantized models and imperfect optimization algorithms commonly used in practical contexts for system identification, and in particular hybrid system identification. Two families of bounds are obtained: slow-rate bounds via a block decomposition and fast-rate, variance-adaptive, bounds via a novel spaced-point strategy. The bounds scale with the number of bits required to encode the model and thus translate hardware constraints into interpretable statistical complexities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_15586 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Uniform error bounds for quantized dynamical models Metakalard, Abdelkader Lauer, Fabien Colin, Kevin Gilson, Marion Machine Learning This paper provides statistical guarantees on the accuracy of dynamical models learned from dependent data sequences. Specifically, we develop uniform error bounds that apply to quantized models and imperfect optimization algorithms commonly used in practical contexts for system identification, and in particular hybrid system identification. Two families of bounds are obtained: slow-rate bounds via a block decomposition and fast-rate, variance-adaptive, bounds via a novel spaced-point strategy. The bounds scale with the number of bits required to encode the model and thus translate hardware constraints into interpretable statistical complexities. |
| title | Uniform error bounds for quantized dynamical models |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2602.15586 |