7 citations · 17 across the 9 of their papers we have counts for
9 papers
Generating gradients in the energy landscape using rectified linear type cost functions for efficiently solving 0/1 matrix factorization in Simulated Annealing
Makiko Konoshima, Hirotaka Tamura, Yoshiyuki Kabashima
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…
Characterization of Locality in Spin States and Forced Moves for Optimizations
Yoshiki Sato, Makiko Konoshima, Hirotaka Tamura +1
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 c…
Efficient correlation-based discretization of continuous variables for annealing machines
Yuki Furue, Makiko Konoshima, Hirotaka Tamura +1
Annealing machines specialized for combinatorial optimization problems have been developed, and some companies offer services to use those machines. Such specialized machines can o…
Derivation of QUBO formulations for sparse estimation
Tomohiro Yokota, Makiko Konoshima, Hirotaka Tamura +1
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 qu…
Quadratic unconstrained binary optimization formulation for rectified-linear-unit-type functions
Go Sato, Makiko Konoshima, Takuya Ohwa +2
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 e…
Eclipse Hashing: Alexandrov Compactification and Hashing with Hyperspheres for Fast Similarity Search
Yui Noma, Makiko Konoshima
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 sear…