Zobrazeno 1 - 10
of 80
pro vyhledávání: '"SATO, Rei"'
Autor:
Sato, Rei, Saito, Kazuhiro
In this paper, we propose a circuit design for implementing quantum walks on complex networks. Quantum walks are powerful tools for various graph-based applications such as spatial search, community detection, and node classification. Although many q
Externí odkaz:
http://arxiv.org/abs/2408.15653
In this paper, we propose QWalkVec, a quantum walk-based node embedding method. A quantum walk is a quantum version of a random walk that demonstrates a faster propagation than a random walk on a graph. We focus on the fact that the effect of the dep
Externí odkaz:
http://arxiv.org/abs/2408.08534
Autor:
Sato, Rei, Cui, Gordon, Saito, Kazuhiro, Kawashima, Hideyuki, Nikuni, Tetsuro, Watabe, Shohei
Quantum search algorithms, such as Grover's algorithm, are anticipated to efficiently solve constrained combinatorial optimization problems. However, applying these algorithms to the traveling salesman problem (TSP) on a quantum circuit presents a si
Externí odkaz:
http://arxiv.org/abs/2405.07129
Safety and trustworthiness are indispensable requirements for real-world applications of AI systems using large language models (LLMs). This paper formulates human value alignment as an optimization problem of the language model policy to maximize re
Externí odkaz:
http://arxiv.org/abs/2404.11049
Since quantum spatial searches on complex networks have a strong network dependence, the question arises whether the universal perspective exists in this quantum algorithm for complex networks. Here, we uncover the universal scaling laws of the quant
Externí odkaz:
http://arxiv.org/abs/2401.11922
We investigate policy transfer using image-to-semantics translation to mitigate learning difficulties in vision-based robotics control agents. This problem assumes two environments: a simulator environment with semantics, that is, low-dimensional and
Externí odkaz:
http://arxiv.org/abs/2301.13343
In the field of reinforcement learning, because of the high cost and risk of policy training in the real world, policies are trained in a simulation environment and transferred to the corresponding real-world environment. However, the simulation envi
Externí odkaz:
http://arxiv.org/abs/2211.03413
Neural architecture search (NAS) is an approach for automatically designing a neural network architecture without human effort or expert knowledge. However, the high computational cost of NAS limits its use in commercial applications. Two recent NAS
Externí odkaz:
http://arxiv.org/abs/2012.06138
Autor:
Sakamoto, Kotaro, Ishibashi, Hideaki, Sato, Rei, Shirakawa, Shinichi, Akimoto, Youhei, Hino, Hideitsu
Publikováno v:
In Neural Networks September 2023 166:446-458
Publikováno v:
Phys. Rev. A 101, 022312 (2020)
We investigate a quantum spatial search problem on fractal lattices, such as Sierpinski carpets and Menger sponges. In earlier numerical studies of the Sierpinski gasket, the Sierpinski tetrahedron, and the Sierpinski carpet, conjectures have been pr
Externí odkaz:
http://arxiv.org/abs/1908.11827