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Haydn T. Jones

2 accepted papers

2024

Large-Scale Gaussian Processes via Alternating Projection

AISTATS 2024poster

Training and inference in Gaussian processes (GPs) require solving linear systems with $n\times n$ kernel matrices. To address the prohibitive $\mathcal{O}(n^3)$ time complexity, recent work has employed fast iterative methods, like conjugate gradients (CG). However, as datasets increase in magnitud…

2022

If you’ve trained one you’ve trained them all: inter-architecture similarity increases with robustness

UAI 2022poster

Previous work has shown that commonly-used metrics for comparing representations between neural networks overestimate similarity due to correlations between data points. We show that intra-example feature correlations also causes significant overestimation of network similarity and propose an image…