output
20132022
most citedDynamics of reverse annealing for the fully-connected -spin model

79 citations

9 papers

cs.PF2022★ 19 cited

Diverse Adaptive Bulk Search: a Framework for Solving QUBO Problems on Multiple GPUs

Koji Nakano, Daisuke Takafuji, Yasuaki Ito +5

Quadratic Unconstrained Binary Optimization (QUBO) is a combinatorial optimization to find an optimal binary solution vector that minimizes the energy value defined by a quadratic…

quant-ph2021★ 2 cited

Solving Large Break Minimization Problems in a Mirrored Double Round-robin Tournament Using Quantum Annealing

Michiya Kuramata, Ryota Katsuki, Kazuhide Nakata

Quantum annealing (QA) has gained considerable attention because it can be applied to combinatorial optimization problems, which have numerous applications in logistics, scheduling…

quant-ph2020★ 22 cited

Larger Sparse Quadratic Assignment Problem Optimization Using Quantum Annealing and a Bit-Flip Heuristic Algorithm

Michiya Kuramata, Ryota Katsuki, Kazuhide Nakata

Quantum annealing and D-Wave quantum annealer attracted considerable attention for their ability to solve combinatorial optimization problems. In order to solve other type of optim…

cs.SE2020★ 15 cited

PATSQL: Efficient Synthesis of SQL Queries from Example Tables with Quick Inference of Projected Columns

Keita Takenouchi, Takashi Ishio, Joji Okada +1

SQL is one of the most popular tools for data analysis, and it is now used by an increasing number of users without having expertise in databases. Several studies have proposed pro…

quant-ph2019★ 79 cited

Dynamics of reverse annealing for the fully-connected -spin model

Yu Yamashiro, Masaki Ohkuwa, Hidetoshi Nishimori +1

Reverse annealing is a relatively new variant of quantum annealing, in which one starts from a classical state and increases and then decreases the amplitude of the transverse fiel…

cs.CV2019★ 19 cited

Brain-mediated Transfer Learning of Convolutional Neural Networks

Satoshi Nishida, Yusuke Nakano, Antoine Blanc +3

The human brain can effectively learn a new task from a small number of samples, which indicate that the brain can transfer its prior knowledge to solve tasks in different domains.…

math.ST2018★ 9 cited

Variational Approximation Error in Bayesian Non-negative Matrix Factorization

Naoki Hayashi

Non-negative matrix factorization (NMF) is a knowledge discovery method that is used in many fields. Variational inference and Gibbs sampling methods for it are also wellknown. How…

math.ST2017★ 4 cited

Asymptotic Bayesian Generalization Error in Latent Dirichlet Allocation and Stochastic Matrix Factorization

Naoki Hayashi, Sumio Watanabe

Latent Dirichlet allocation (LDA) is useful in document analysis, image processing, and many information systems; however, its generalization performance has been left unknown beca…

cs.CV2013

A Face-like Structure Detection on Planet and Satellite Surfaces using Image Processing

Kazutaka Kurihara, Masakazu Takasu, Kazuhiro Sasao +5

This paper demonstrates that face-like structures are everywhere, and can be de-tected automatically even with computers. Huge amount of satellite images of the Earth, the Moon, th…