4 papers
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…
Near-Optimal Approximations for Bayesian Inference in Function Space
Veit Wild, James Wu, Dino Sejdinovic +1
We propose a scalable inference algorithm for Bayes posteriors defined on a reproducing kernel Hilbert space (RKHS). Given a likelihood function and a Gaussian random element repre…
Indirect Query Bayesian Optimization with Integrated Feedback
Mengyan Zhang, Shahine Bouabid, Cheng Soon Ong +2
We develop the framework of Indirect Query Bayesian Optimization (IQBO), a new class of Bayesian optimization problems where the integrated feedback is given via a conditional expe…
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…