1 citations · 2 across the 6 of their papers we have counts for
6 papers
Non-Parametric Model Calibration with Stochastic Control Parameters
Akshay Prasadan, Samopriya Basu, Faezeh Yazdi +2
We present a method for calibrating a computer model using non-parametric techniques where the inputs are stochastic but include calibration parameters whose distributions are unkn…
Robust mean estimation under star-shaped constraints with heavy-tailed noise
Tuorui Peng, Akshay Prasadan, Matey Neykov
We study the problem of robust mean estimation with adversarially contaminated data under star-shaped constraints in a heavy-tailed noise setting, where only a finite second moment…
Continuity of the Solution of a Non-Parametric Bayesian Statistical Calibration Procedure
Akshay Prasadan, Donald Estep, Derek Bingham
Recent work has developed a non-parametric Bayesian approach to the calibration of a computer model, which abstractly amounts to the inversion of a pushforward of stochastic input…
Information theoretic limits of robust sub-Gaussian mean estimation under star-shaped constraints
Akshay Prasadan, Matey Neykov
We obtain the minimax rate for a mean location model with a bounded star-shaped set constraint on the mean, in an adversarially corrupted data setting wi…
Some facts about the optimality of the LSE in the Gaussian sequence model with convex constraint
Akshay Prasadan, Matey Neykov
We consider a convex constrained Gaussian sequence model and characterize necessary and sufficient conditions for the least squares estimator (LSE) to be minimax optimal. For a clo…
Characterizing the minimax rate of nonparametric regression under bounded star-shaped constraints
Akshay Prasadan, Matey Neykov
We quantify the minimax rate for a nonparametric regression model over a star-shaped function class with bounded diameter. We obtain a minimax rate of ${\varepsilon^{…