Exploring Discovering Black Box Optimizers Via Evolutionary Meta Learning
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- IEEE ESCO Webinar #16:
- by Gjorgjina Cenikj, Ana Nikolikj, Tome Eftimov.
- Many real-world optimization challenges are significantly harder than the scenarios that can be rigorously analyzed by ...
- For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai To follow along with the course, ...
- Spring 2021 SIP Seminar Series: April 21, 2021 [http://www.inspirelab.us/seminars/] Speaker: Prof. Tara Javidi Abstract: In this talk ...
In-Depth Information on Discovering Black Box Optimizers Via Evolutionary Meta Learning
Title: Abstract: Optimizing functions without access to gradients is the remit of Jascha Sohl-Dickstein (Google Brain) https://simons.berkeley.edu/talks/tbd-60 Frontiers of Deep Kirsch Louis, Sebastian Flennerhag, Hado van Hasselt, Abram Friesen, Junhyuk Oh, and Yutian Chen. "Introducing Symmetries to ...
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