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09/06/2023
Random postprocessing for combinatorial Bayesian optimization
Model-based sequential approaches to discrete "black-box" optimization, ...
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04/25/2022
Travel time optimization on multi-AGV routing by reverse annealing
Quantum annealing has been actively researched since D-Wave Systems prod...
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01/31/2022
Sparse Signal Reconstruction with QUBO Formulation in l0-regularized Linear Regression
An l0-regularized linear regression for a sparse signal reconstruction i...
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03/15/2021
Assessment of image generation by quantum annealer
Quantum annealing was originally proposed as an approach for solving com...
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02/24/2021
Kernel-based framework to estimate deformations of pneumothorax lung using relative position of anatomical landmarks
In video-assisted thoracoscopic surgeries, successful procedures of nodu...
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07/16/2020
Maximum-Likelihood Channel Decoding with Quantum Annealing Machine
We formulate maximum likelihood (ML) channel decoding as a quadratic unc...
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02/13/2020
Breaking limitation of quantum annealer in solving optimization problems under constraints
Quantum annealing is a generic solver for optimization problems that use...
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01/21/2019
Message-passing algorithm of quantum annealing with nonstoquastic Hamiltonian
Quantum annealing (QA) is a generic method for solving optimization prob...
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12/04/2018
Control of automated guided vehicles without collision by quantum annealer and digital devices
We formulate an optimization problem to control a large number of automa...
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07/01/2018
Optimization of neural networks via finite-value quantum fluctuations
We numerically test an optimization method for deep neural networks (DNN...
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03/20/2018
Momentum-Space Renormalization Group Transformation in Bayesian Image Modeling by Gaussian Graphical Model
A new Bayesian modeling method is proposed by combining the maximization...
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11/28/2017
Deformation estimation of an elastic object by partial observation using a neural network
Deformation estimation of elastic object assuming an internal organ is i...
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02/10/2017
Sparse modeling approach to analytical continuation of imaginary-time quantum Monte Carlo data
A new approach of solving the ill-conditioned inverse problem for analyt...
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02/10/2017
Compressing Green's function using intermediate representation between imaginary-time and real-frequency domains
New model-independent compact representations of imaginary-time data are...
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11/19/2015
Stochastic gradient method with accelerated stochastic dynamics
In this paper, we propose a novel technique to implement stochastic grad...
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03/11/2015
L_1-regularized Boltzmann machine learning using majorizer minimization
We propose an inference method to estimate sparse interactions and biase...
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01/19/2015
Statistical-mechanical analysis of pre-training and fine tuning in deep learning
In this paper, we present a statistical-mechanical analysis of deep lear...
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01/05/2015
Inverse Renormalization Group Transformation in Bayesian Image Segmentations
A new Bayesian image segmentation algorithm is proposed by combining a l...
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10/14/2014