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Fuzzy Clustering for QAOA Complexity Reduction
2023 IEEE International Conference on Fuzzy Systems (FUZZ), 2023The Quantum Approximate Optimization Algorithm (QAOA) has become one of the most widely used components in the development of modern quantum applications. It works on the paradigm of quantum variational circuits, where a quantum circuit is trained - by repeatedly adjusting circuit parameters - to adequately solve a combinatorial optimization problem ...
Acampora G., Chiatto A., Vitiello A.
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Quantum Approximate Optimization Algorithm (QAOA)
2023Ramin Fakhimi, Hamidreza Validi
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QAOA-based MRMR Algorithm for Feature Selection
Proceedings of the 2023 International Conference on Advances in Artificial Intelligence and Applications, 2023Xinyu Jiang +5 more
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Correctness of an application using QAOA
In this work, we analyze the Quantum Approximate Optimization Algorithm (QAOA) to solve a particular type of problem related to a graph clustering. We establish rigorous bounds for the efficiency of QAOA in the limit of a large problem.Reittu, Hannu, Kotovirta, Ville
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Practice and Experience in Advanced Research Computing 2025: The Power of Collaboration
Shin-Wei Chiu +6 more
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Shin-Wei Chiu +6 more
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Personalized Course Selection Optimization Using QAOA
2025 IEEE International Conference on Consumer Electronics (ICCE)Takeru Ota +3 more
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AI-Augmented Parameter Initialization for QAOA
2025 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W)Jai Nana +8 more
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Parameter Transfers for Warm-Started QAOA
Proceedings of the 1st International Conference on Quantum SoftwareJulian Obst +3 more
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