no code implementations • 7 Feb 2016 • Michael Brand, David L. Dowe
We introduce a problem set-up we call the Iterated Matching Pennies (IMP) game and show that it is a powerful framework for the study of three problems: adversarial learnability, conventional (i. e., non-adversarial) learnability and approximability.
no code implementations • 14 Oct 2016 • Michael Brand
Strict Minimum Message Length (SMML) is an information-theoretic statistical inference method widely cited (but only with informal arguments) as providing estimations that are consistent for general estimation problems.
no code implementations • 20 Jul 2017 • Michael Brand
Neyman-Scott is a classic example of an estimation problem with a partially-consistent posterior, for which standard estimation methods tend to produce inconsistent results.
no code implementations • 28 Jun 2018 • Michael Brand
We define a new class of Bayesian point estimators, which we refer to as risk averse.