no code implementations • 2 May 2024 • Sam Reifenstein, Timothee Leleu, Yoshihisa Yamamoto
We propose a novel algorithm that extends the methods of ball smoothing and Gaussian smoothing for noisy derivative-free optimization by accounting for the heterogeneous curvature of the objective function.
no code implementations • 17 Oct 2023 • Mostafa Honari Latifpour, Byoung Jun Park, Yoshihisa Yamamoto, Myoung-Gyun Suh
The rapid advancements in machine learning across numerous industries have amplified the demand for extensive matrix-vector multiplication operations, thereby challenging the capacities of traditional von Neumann computing architectures.
no code implementations • 9 Mar 2021 • Edwin Ng, Tatsuhiro Onodera, Satoshi Kako, Peter L. McMahon, Hideo Mabuchi, Yoshihisa Yamamoto
We show that the nonlinear stochastic dynamics of a measurement-feedback-based coherent Ising machine (MFB-CIM) in the presence of quantum noise can be exploited to sample degenerate ground and low-energy spin configurations of the Ising model.
Quantum Physics Optics