2 papers
cs.LG2023
PAC Prediction Sets for Large Language Models of Code
Adam Khakhar, Stephen Mell, Osbert Bastani
Prediction sets have recently been shown to be a promising strategy for quantifying the uncertainty of deep neural networks in a way that provides theoretical guarantees. However,…
cs.LG2022
Neural Regression For Scale-Varying Targets
Adam Khakhar, Jacob Buckman
In this work, we demonstrate that a major limitation of regression using a mean-squared error loss is its sensitivity to the scale of its targets. This makes learning settings cons…