Invention Grant
- Patent Title: Systems and methods for parallelizing Bayesian optimization
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Application No.: US14291337Application Date: 2014-05-30
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Publication No.: US10346757B2Publication Date: 2019-07-09
- Inventor: Ryan P. Adams , Roland Jasper Snoek , Hugo Larochelle
- Applicant: Universite de Sherbrooke , President and Fellows of Harvard College , Governing Council of the Univ. of Toronto, The
- Applicant Address: US MA Cambridge CA Sherbrooke, Quebec CA Toronto, Ontario
- Assignee: President and Fellows of Harvard College,Socpra Sciences ET Genie S.E.C.,The Governing Council of the University of Toronto
- Current Assignee: President and Fellows of Harvard College,Socpra Sciences ET Genie S.E.C.,The Governing Council of the University of Toronto
- Current Assignee Address: US MA Cambridge CA Sherbrooke, Quebec CA Toronto, Ontario
- Agency: Wolf, Greenfield & Sacks, P.C.
- Main IPC: G06N5/04
- IPC: G06N5/04 ; G06N7/00 ; G06F17/11 ; G06N20/00

Abstract:
Techniques for use in connection with performing optimization using an objective function. The techniques include using at least one computer hardware processor to perform: beginning evaluation of the objective function at a first point; before evaluating the objective function at the first point is completed: identifying, based on likelihoods of potential outcomes of evaluating the objective function at the first point, a second point different from the first point at which to evaluate the objective function; and beginning evaluation of the objective function at the second point.
Public/Granted literature
- US20160328653A1 SYSTEMS AND METHODS FOR PARALLELIZING BAYESIAN OPTIMIZATION Public/Granted day:2016-11-10
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