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Robert F Allison

2 accepted papers

2025

Conditional Distribution Compression via the Kernel Conditional Mean Embedding

NeurIPS 2025poster

Existing distribution compression methods, like Kernel Herding (KH), were originally developed for unlabelled data. However, no existing approach directly compresses the conditional distribution of *labelled* data. To address this gap, we first introduce the *Average Maximum Conditional Mean Discrep…

Cited by 0SourceScholar
2023

Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression

NeurIPS 2023poster

The accurate predictions and principled uncertainty measures provided by GP regression incur $O(n^3)$ cost which is prohibitive for modern-day large-scale applications. This has motivated extensive work on computationally efficient approximations. We introduce a new perspective by exploring robustne…