no code implementations • 24 Feb 2017 • Stephen N. Pallone, Peter I. Frazier, Shane G. Henderson
Under certain noise assumptions, we show that the Bayes-optimal policy for maximally reducing entropy of the posterior distribution of this linear classifier is a greedy policy, and that this policy achieves a linear lower bound when alternatives can be constructed from the continuum.
no code implementations • 12 Dec 2016 • Peter I. Frazier, Shane G. Henderson, Rolf Waeber
The probabilistic bisection algorithm (PBA) solves a class of stochastic root-finding problems in one dimension by successively updating a prior belief on the location of the root based on noisy responses to queries at chosen points.