1 code implementation • 11 Jul 2023 • Etash Kumar Guha, Eugene Ndiaye, Xiaoming Huo
Given a sequence of observable variables $\{(x_1, y_1), \ldots, (x_n, y_n)\}$, the conformal prediction method estimates a confidence set for $y_{n+1}$ given $x_{n+1}$ that is valid for any finite sample size by merely assuming that the joint distribution of the data is permutation invariant.
no code implementations • 30 May 2023 • Etash Kumar Guha, Jason D. Lee
Reinforcement Learning is a powerful framework for training agents to navigate different situations, but it is susceptible to changes in environmental dynamics.
no code implementations • 30 May 2023 • Etash Kumar Guha, Prasanjit Dubey, Xiaoming Huo
In this paper, we derive a novel bound on the generalization error of Magnitude-Based pruning of overparameterized neural networks.