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SUMMARY:Bayesian Optimization - Pawel Budzianowiski\; Brian Trippe
DTSTART:20161124T133000Z
DTEND:20161124T150000Z
UID:TALK68510@talks.cam.ac.uk
CONTACT:Yingzhen Li
DESCRIPTION:Bayesian optimization is a framework for performing optimizati
 on of black box functions\, which is particularly useful when function eva
 luations are expensive and the space of possible solutions is large.   Thi
 s talk is roughly divided into two parts\; first we give an overview of Ba
 yesian optimization\, introducing the approach as well as common function 
 models and acquisition functions.  In the second half of the talk\, we hig
 hlight some of the many recent advances in the field and discuss open prob
 lems. Namely\, we will discuss problems in multitask Bayesian optimization
 \, a recent method of modeling a function with Bayesian neural networks\, 
 and connections with active learning.\nReading:\nThese will be covered in 
 the talk:\n\nA Recent Review on Bayesian Optimization\n\nBayesian Optimiza
 tion with Robust Bayesian Neural Networks (to appear at NIPS 2016)
LOCATION:Engineering Department\, CBL Room 438
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