1 citations · 1 across the 4 of their papers we have counts for
4 papers
Generalising maximum mean discrepancy: kernelised functional Bregman divergences
Russell Tsuchida, Frank Nielsen
Bregman divergences play a pivotal role in statistics, machine learning and computational information geometry. Particularly in the context of machine learning, they are central to…
Squared families: Searching beyond regular probability models
Russell Tsuchida, Jiawei Liu, Cheng Soon Ong +1
We introduce squared families, which are families of probability densities obtained by squaring a linear transformation of a statistic. Squared families are singular, however their…
Generalization Certificates for Adversarially Robust Bayesian Linear Regression
Mahalakshmi Sabanayagam, Russell Tsuchida, Cheng Soon Ong +1
Adversarial robustness of machine learning models is critical to ensuring reliable performance under data perturbations. Recent progress has been on point estimators, and this pape…
Label Distribution Learning using the Squared Neural Family on the Probability Simplex
Daokun Zhang, Russell Tsuchida, Dino Sejdinovic
Label distribution learning (LDL) provides a framework wherein a distribution over categories rather than a single category is predicted, with the aim of addressing ambiguity in la…