Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Konoshima, Makiko"'
Publikováno v:
J. Phys. Soc. Jpn., Vol.93, No.4, Article ID: 044002 (2024)
The 0/1 matrix factorization defines matrix products using logical AND and OR as product-sum operators, revealing the factors influencing various decision processes. Instances and their characteristics are arranged in rows and columns. Formulating ma
Externí odkaz:
http://arxiv.org/abs/2312.17272
Publikováno v:
J. Phys. Soc. Jpn. 93, 044802 (2024)
Ising formulations are widely utilized to solve combinatorial optimization problems, and a variety of quantum or semiconductor-based hardware has recently been made available. In combinatorial optimization problems, the existence of local minima in e
Externí odkaz:
http://arxiv.org/abs/2312.02544
Publikováno v:
J. Phys. Soc. Jpn. 92, 044802 (2023)
Annealing machines specialized for combinatorial optimization problems have been developed, and some companies offer services to use those machines. Such specialized machines can only handle binary variables, and their input format is the quadratic u
Externí odkaz:
http://arxiv.org/abs/2301.07244
Publikováno v:
J. Phys. Soc. Jpn. 89, 034801 (2020)
We propose a quadratic unconstrained binary optimization (QUBO) formulation of the l1-norm, which enables us to perform sparse estimation of Ising-type annealing methods such as quantum annealing. The QUBO formulation is derived using the Legendre tr
Externí odkaz:
http://arxiv.org/abs/2001.03715
Publikováno v:
Phys. Rev. E 99, 042106 (2019)
We propose a quadratic unconstrained binary optimization (QUBO) formulation of rectified linear unit (ReLU) type functions. Different from the q-loss function proposed by Denchev et al. (2012), a simple discussion based on the Legendre duality is not
Externí odkaz:
http://arxiv.org/abs/1811.03829
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Akademický článek
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Autor:
Noma, Yui, Konoshima, Makiko
The similarity searches that use high-dimensional feature vectors consisting of a vast amount of data have a wide range of application. One way of conducting a fast similarity search is to transform the feature vectors into binary vectors and perform
Externí odkaz:
http://arxiv.org/abs/1406.3882
Autor:
Noma, Yui, Konoshima, Makiko
Since Hamming distances can be calculated by bitwise computations, they can be calculated with less computational load than L2 distances. Similarity searches can therefore be performed faster in Hamming distance space. The elements of Hamming distanc
Externí odkaz:
http://arxiv.org/abs/1303.4169
Autor:
Konoshima, Makiko, Noma, Yui
Locality-sensitive hashing converts high-dimensional feature vectors, such as image and speech, into bit arrays and allows high-speed similarity calculation with the Hamming distance. There is a hashing scheme that maps feature vectors to bit arrays
Externí odkaz:
http://arxiv.org/abs/1212.6110