Results 21 to 30 of about 1,190 (203)
Distance-based clustering using QUBO formulations [PDF]
Scientific Reports, 2022 AbstractIn computer science, clustering is a technique for grouping data. Ising machines can solve distance-based clustering problems described by quadratic unconstrained binary optimization (QUBO) formulations. A typical simple method using an Ising machine makes each cluster size equal and is not suitable for clustering unevenly distributed data.
Nasa Matsumoto +3 more
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QUBO formulations for training machine learning models [PDF]
Scientific Reports, 2021 AbstractTraining machine learning models on classical computers is usually a time and compute intensive process. With Moore’s law nearing its inevitable end and an ever-increasing demand for large-scale data analysis using machine learning, we must leverage non-conventional computing paradigms like quantum computing to train machine learning models ...
Prasanna Date +2 more
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IEEE Access, 2023 Quantum annealing has the potential to outperform classical transistor-based computer technologies in tackling intricate combinatorial optimization problems. However, ongoing scientific debates cast doubts on whether quantum annealing devices (or quantum
Jehn-Ruey Jiang, Chun-Wei Chu
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Pattern QUBOs: Algorithmic Construction of 3SAT-to-QUBO Transformations
Electronics, 2023 One way of solving 3sat instances on a quantum computer is to transform the 3sat instances into instances of Quadratic Unconstrained Binary Optimizations (QUBOs), which can be used as an input for the QAOA algorithm on quantum gate systems or as an input for quantum annealers. This mapping is performed by a 3sat-to-QUBO transformation. Recently, it has
Sebastian Zielinski +5 more
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Quadratic Unconstrained Binary Optimization for the Automotive Paint Shop Problem
IEEE Access, 2023 The Binary Paint Shop Problem (BPSP) is a combinatorial optimization problem which draws inspiration from the automotive paint shop. Its binary nature, making it a good fit for Quadratic Unconstrained Binary Optimization (QUBO) solvers, has been well ...
Pieter Debevere +2 more
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Searching for an Efficient System of Equations Defining the AES Sbox for the QUBO Problem
Journal of Telecommunications and Information Technology, 2023 The time complexity of solving the QUBO problem depends mainly on the number of logical variables in the problem. This paper focuses mainly on finding a system of equations that uniquely defines the Sbox of the AES cipher and simultaneously allows us to
Elżbieta Burek +2 more
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GPS: A New TSP Formulation for Its Generalizations Type QUBO
Mathematics, 2022 We propose a new Quadratic Unconstrained Binary Optimization (QUBO) formulation of the Travelling Salesman Problem (TSP), with which we overcame the best formulation of the Vehicle Routing Problem (VRP) in terms of the minimum number of necessary ...
Saul Gonzalez-Bermejo +2 more
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A QUBO Framework for Team Formation [PDF]
The team formation problem assumes a set of experts and a task, where each expert has a set of skills and the task requires some skills. The objective is to find a set of experts that maximizes coverage of the required skills while simultaneously minimizing the costs associated with the experts.
Karan Vombatkere +2 more
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Posiform planting: generating QUBO instances for benchmarking
Frontiers in Computer Science, 2023 We are interested in benchmarking both quantum annealing and classical algorithms for minimizing quadratic unconstrained binary optimization (QUBO) problems. Such problems are NP-hard in general, implying that the exact minima of randomly generated instances are hard to find and thus typically unknown. While brute forcing smaller instances is possible,
Georg Hahn +3 more
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Derivation of QUBO Formulations for Sparse Estimation [PDF]
Journal of the Physical Society of Japan, 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 transformation and the Wolfe theorem, which have recently been employed to derive the QUBO formulations of
Yokota, Tomohiro +3 more
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