Bayesian Optimisation Reading Group
War-BORG - The Warwick Bayesian-Optimisation Reading Group is an academic research study group based at the University of Warwick, UK. The research group consists of PhD students and professors with Mathematics, Statistics and Computer Science backgrounds, including members of the Complexity Science Dept., Warwick Business School and Mathematics Institute.
Previous Reading Groups:
Laura Guzman presented her work on ...
Juan Ungredda presented his recent work on BICO, an algorithm recently submitted for publication that balances the improvement of objective value prediction with improvement of input uncertainty in order to allocate search budget accordingly.
Hoai Phuong Le presented recent work on Bayesian Optimisation for finding the robust solution of a black-box function. The algorithm uses a variant of the well-known Knowledge Gradient as the acquisition function.
Michael Pearce presented his recent work on ConBO, an algorithm recently submitted for publication that combines 2 methods of computing well-known Knowledge Gradient: by discretisation and by simulation.
Sebastian Gonzalez presented his work on multiobjective Bayesian Optimisation.
Yuri Marca presented a paper ...
Hoai Phuong Le presented some papers about Entropy Search, another well-known acquisition function for Bayesian Optimisation.
--- Reading Group continued online ---
for previous Topics click here
2020 : Kent, Branke - BOP-Elites, a Bayesian Optimisation algorithm for Quality-Diversity search. LINK
2018 : Pearce,Branke - Continuous multi-task Bayesian Optimisation with correlation. LINK
Contact and code:
This page is maintained by members of the group, primarily Paul Kent. Feel free to contact.
Much of the code and papers from recent talks can be found here (contact Danielle for access):
via Microsoft Teams
Please contact one of the below members for access.
Juan Ungredda (PhD Student)
Michael Pearce (PhD Student)
Danielle Varjosalmi (PhD Student)
Hoai Phuong Le (PhD Student)
Paul Kent (PhD Student)