Operator-adaptive PLS and Ridge models integrate linear preprocessing screening internally via algebraic identities, delivering comparable or better prediction accuracy than exhaustive external search on NIR regression and classification tasks with orders-of-magnitude lower fitting time.
Kowalski , abstract =
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
On-policy distillation gains efficiency from early foresight in module allocation and update directions, which the proposed EffOPD method exploits for 3x faster training with comparable performance.
citing papers explorer
-
Reframing preprocessing selection as model-internal calibration in near-infrared spectroscopy: A large-scale benchmark of operator-adaptive PLS and Ridge models
Operator-adaptive PLS and Ridge models integrate linear preprocessing screening internally via algebraic identities, delivering comparable or better prediction accuracy than exhaustive external search on NIR regression and classification tasks with orders-of-magnitude lower fitting time.
-
Learning to Foresee: Unveiling the Unlocking Efficiency of On-Policy Distillation
On-policy distillation gains efficiency from early foresight in module allocation and update directions, which the proposed EffOPD method exploits for 3x faster training with comparable performance.