no code implementations • 21 Mar 2023 • Dusan Gostimirovic, Yuri Grinberg, Dan-Xia Xu, Odile Liboiron-Ladouceur
Without modifying the nanofabrication process, adding significant computation in design, or requiring proprietary process specifications, we believe our model opens the door to new levels of reliability and performance in next-generation photonic circuits.
no code implementations • 23 May 2022 • Muhammad Al-Digeil, Yuri Grinberg, Daniele Melati3, Mohsen Kamandar Dezfouli, Jens H. Schmid, Pavel Cheben, Siegfried Janz, Dan-Xia Xu
We show that our proposed approach is substantially better than both PCA and randomly initialized AE in the majority of low-data regime cases we consider, or at least is comparable to the best of either of the other two methods.
no code implementations • NeurIPS 2014 • Yuri Grinberg, Doina Precup, Michel Gendreau
We consider the challenging practical problem of optimizing the power production of a complex of hydroelectric power plants, which involves control over three continuous action variables, uncertainty in the amount of water inflows and a variety of constraints that need to be satisfied.
no code implementations • NeurIPS 2013 • Mahdi Milani Fard, Yuri Grinberg, Amir-Massoud Farahmand, Joelle Pineau, Doina Precup
This paper addresses the problem of automatic generation of features for value function approximation in reinforcement learning.