Daniel Brice - Thompson Sampling

Daniel Brice will present "On the likelihood that one unknown probability exceeds another in view of the evidence of two samples" by William Thompson. It gives a solution to the multi-armed bandit problem that gives O(log(n)) regret that is today used in machine learning applications and goes by the name "Thompson Sampling" in this author's honor. Contrast this to A/B Testing, another multi-armed bandit algorithm that gives much worse O(n) regret.

https://www.dropbox.com/s/yhn9prnr5bz0156/1933-thompson.pdf