%0 Conference Proceedings
%T Semantic Classification and Learning Using a Linear Tranformation Model in a Probabilistic Type Theory with Records
%A Larsson, Staffan
%A Bernardy, Jean-Philippe
%Y Howes, Christine
%Y Dobnik, Simon
%Y Breitholtz, Ellen
%Y Chatzikyriakidis, Stergios
%S Proceedings of the Reasoning and Interaction Conference (ReInAct 2021)
%D 2021
%8 October
%I Association for Computational Linguistics
%C Gothenburg, Sweden
%F larsson-bernardy-2021-semantic
%X Starting from an existing account of semantic classification and learning from interaction formulated in a Probabilistic Type Theory with Records, encompassing Bayesian inference and learning with a frequentist flavour, we observe some problems with this account and provide an alternative account of classification learning that addresses the observed problems. The proposed account is also broadly Bayesian in nature but instead uses a linear transformation model for classification and learning.
%U https://aclanthology.org/2021.reinact-1.3
%P 14-22