Deterministic Bounds on Accuracy and Stability of Metric-Space Regression and Classification
arXiv:2610.22564v1 Announce Type: new Abstract: Data-driven approaches often face ambiguity in datasets due to sensor or target noise, insufficient information, and noise in the input data. While best-fit machine learning methods can accommodate such noise through uncertainty estimates, they are pr…
Read the full story at arXiv cs.LG ↗
Timeline · 1 report
- 2026-10-19 04:00 · arXiv cs.LG
Deterministic Bounds on Accuracy and Stability of Metric-Space Regression and Classification