تقرير
Lightsolver challenges a leading deep learning solver for Max-2-SAT problems
| العنوان: | Lightsolver challenges a leading deep learning solver for Max-2-SAT problems |
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| المؤلفون: | Wirzberger, Hod, Kalinski, Assaf, Meirzada, Idan, Primack, Harel, Romano, Yaniv, Tradonsky, Chene, Shlomi, Ruti Ben |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science Quantum Physics |
| مصطلحات موضوعية: | Quantum Physics, Computer Science - Machine Learning |
| الوصف: | Maximum 2-satisfiability (MAX-2-SAT) is a type of combinatorial decision problem that is known to be NP-hard. In this paper, we compare LightSolver's quantum-inspired algorithm to a leading deep-learning solver for the MAX-2-SAT problem. Experiments on benchmark data sets show that LightSolver achieves significantly smaller time-to-optimal-solution compared to a state-of-the-art deep-learning algorithm, where the gain in performance tends to increase with the problem size. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2302.06926 |
| رقم الأكسشن: | edsarx.2302.06926 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |