The Conference on Uncertainty in Artificial Intelligence (UAI) has been established since 1985, this year it will be held from July 17-29 as a virtual event. UAI is one of the foremost international conferences related to knowledge representation, learning and reasoning in uncertainty in machine learning.
Eric Lee, SigOpt Research Engineer, David Eriksson, Facebook Research Scientist, and Valerio Perrone and Matthias Seeger, Amazon Applied Research Scientists, collaborated on a paper on cost-constrained Bayesian optimization that has been accepted at UAI. Bayesian optimization budgets are normally given in iterations while assuming each evaluation has the same cost. Cost-constrained Bayesian optimization measures convergence with alternative cost metrics such as time, money or energy.
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We hope to see you at the event!