We are pleased to announce an upcoming evaluation of probabilistic approximate inference algorithms and machine learning multi-label classification algorithms as part of the UAI 2022 conference.

Evaluation Tasks

  • PR: computation of the partition function
  • MAR: computation of marginal probabilities
  • MAP: computation the most likely assignment over all variables
  • MMAP: computation the most likely assignment to a subset of variables maximizing the MAR on the remaining variables
  • MLC: multi-label classification of a subset of variables

Organizers

Rina Dechter (University of California, Irvine)
Alexander Ihler (University of California, Irvine)
Vibhav Gogate (University of Texas, Dallas)
Junkyu Lee (IBM Research)
Bobak Pezeshki (University of California, Irvine)
Annie Raichev (University of California, Irvine)
Nick Cohen (University of California, Irvine)

Contact: uaicompetition at gmail dot com