1 citations · 1 across the 6 of their papers we have counts for
6 papers
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…
Berry-Esseen bounds for multivariate martingale difference sequences in the Kolmogorov distance
Weichen Wu, Dung Le, Arun Kumar Kuchibhotla +1
We derive new Gaussian approximations for finite martingale difference sequences in with respect to the Kolmogorov distance. Under appropriate conditions, our bounds…
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…
Uncertainty quantification for Markov chain induced martingales with application to temporal difference learning
Weichen Wu, Yuting Wei, Alessandro Rinaldo
We establish novel and general high-dimensional concentration inequalities and Berry-Esseen bounds for vector-valued martingales induced by Markov chains. We apply these results to…
Statistical Inference for Policy Evaluation with Temporal Difference Learning
Weichen Wu, Gen Li, Yuting Wei +1
We investigate the statistical properties of Temporal Difference (TD) learning with Polyak-Ruppert averaging, arguably one of the most widely used algorithms in reinforcement learn…
On the estimation of persistence intensity functions and linear representations of persistence diagrams
Weichen Wu, Jisu Kim, Alessandro Rinaldo
The prevailing statistical approach to analyzing persistence diagrams is concerned with filtering out topological noise. In this paper, we adopt a different viewpoint and aim at es…