13 citations · 13 across the 5 of their papers we have counts for
5 papers
Reshaping Global Loop Structure to Accelerate Local Optimization by Smoothing Rugged Landscapes
Timothee Leleu, Sam Reifenstein, Atsushi Yamamura +1
Probabilistic graphical models with frustration exhibit rugged energy landscapes that trap iterative optimization dynamics. These landscapes are shaped not only by local interactio…
Neural Ising Machines via Unrolling and Zeroth-Order Training
Sam Reifenstein, Timothee Leleu
We propose a data-driven heuristic for NP-hard Ising and Max-Cut optimization that learns the update rule of an iterative dynamical system. The method learns a shared, node-wise up…
Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization
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…
Coherent Ising Machines with Optical Error Correction Circuits
Sam Reifenstein, Satoshi Kako, Farad Khoyratee +2
We propose a network of open-dissipative quantum oscillators with optical error correction circuits. In the proposed network, the squeezed/anti-squeezed vacuum states of the consti…
A Benchmarking Study of Quantum Algorithms for Combinatorial Optimization
Krishanu Sankar, Artur Scherer, Satoshi Kako +8
We study the performance scaling of three quantum algorithms for combinatorial optimization: measurement-feedback coherent Ising machines (MFB-CIM), discrete adiabatic quantum comp…