Showing math.STShow all
3 papers · 1 filter
math.ST2026
Prediction-Only Distillation in Linear and Logistic Regression
Hien Dang, Pratik Patil, Alessandro Rinaldo
Self-distillation (SD) is typically studied when the student is retrained on the teacher's original training inputs. In many practical deployments, however, the labeled training da…
math.ST2026
Optimal Unconstrained Self-Distillation in Ridge Regression: Strict Improvements, Precise Asymptotics, and One-Shot Tuning
Hien Dang, Pratik Patil, Alessandro Rinaldo
Self-distillation (SD) is the process of retraining a student on a mixture of ground-truth labels and the teacher's own predictions using the same architecture and training data. A…
math.ST2023
Asymptotically free sketched ridge ensembles: Risks, cross-validation, and tuning
Pratik Patil, Daniel LeJeune
We employ random matrix theory to establish consistency of generalized cross validation (GCV) for estimating prediction risks of sketched ridge regression ensembles, enabling effic…