ADOWIP uses a decision-loss priority gate to update only when loss exceeds an empirical quantile under budget constraints, showing lower held-out decision loss than always-update or fixed-period baselines on ETT tasks.
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, ADS Track , year =
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Adapt Only When It Pays: Budgeted Decision-Loss Priority for Delayed Online Time-Series Adaptation
ADOWIP uses a decision-loss priority gate to update only when loss exceeds an empirical quantile under budget constraints, showing lower held-out decision loss than always-update or fixed-period baselines on ETT tasks.