Andrew McRae — accepted AI-conference papers

2023

Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning

Austin Xu, Andrew McRae, Jingyan Wang, Mark A. Davenport, Ashwin Pananjady

NeurIPS 2023poster

We introduce a new type of query mechanism for collecting human feedback, called the perceptual adjustment query (PAQ). Being both informative and cognitively lightweight, the PAQ adopts an inverted measurement scheme, and combines advantages from both cardinal and ordinal queries. We showcase the P…

Cited by 4 Source ↗PDF ↗code ↗Scholar ↗

2020

Sample complexity and effective dimension for regression on manifolds

Andrew McRae, Justin Romberg, Mark Davenport

NeurIPS 2020poster

We consider the theory of regression on a manifold using reproducing kernel Hilbert space methods. Manifold models arise in a wide variety of modern machine learning problems, and our goal is to help understand the effectiveness of various implicit and explicit dimensionality-reduction methods that…

Cited by 11 Source ↗PDF ↗Scholar ↗