Zobrazeno 1 - 10
of 3 769
pro vyhledávání: '"simultaneous perturbation stochastic approximation"'
Guided-SPSA: Simultaneous Perturbation Stochastic Approximation assisted by the Parameter Shift Rule
Autor:
Periyasamy, Maniraman, Plinge, Axel, Mutschler, Christopher, Scherer, Daniel D., Mauerer, Wolfgang
The study of variational quantum algorithms (VQCs) has received significant attention from the quantum computing community in recent years. These hybrid algorithms, utilizing both classical and quantum components, are well-suited for noisy intermedia
Externí odkaz:
http://arxiv.org/abs/2404.15751
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 7860 (2024)
Many systems in the manufacturing industry have spatial distribution characteristics, which correlate with both time and space. Such systems are known as distributed parameter systems (DPSs). Due to the spatiotemporal coupling characteristics, the mo
Externí odkaz:
https://doaj.org/article/f216d638109242f0b5823a55a6f5e8f4
When measuring the value of a function to be minimized is not only expensive but also with noise, the popular simultaneous perturbation stochastic approximation (SPSA) algorithm requires only two function values in each iteration. In this paper, we p
Externí odkaz:
http://arxiv.org/abs/2203.03075
Akademický článek
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Publikováno v:
Frontiers in Energy Research, Vol 10 (2023)
In order to realize the real-time control of photovoltaic power generation smoothly connected to the grid under the condition that the energy storage equipment can operate safely, a control strategy combining the simultaneous perturbation stochastic
Externí odkaz:
https://doaj.org/article/fb4c46a76afa489481e2f182a49e646a
Publikováno v:
Quantum 5, 567 (2021)
The Quantum Fisher Information matrix (QFIM) is a central metric in promising algorithms, such as Quantum Natural Gradient Descent and Variational Quantum Imaginary Time Evolution. Computing the full QFIM for a model with $d$ parameters, however, is
Externí odkaz:
http://arxiv.org/abs/2103.09232
Akademický článek
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Akademický článek
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Few-shot learning is an important research field of machine learning in which a classifier must be trained in such a way that it can adapt to new classes which are not included in the training set. However, only small amounts of examples of each clas
Externí odkaz:
http://arxiv.org/abs/2006.05152
Publikováno v:
Frontiers in Big Data, Vol 5 (2022)
Elasticsearch is currently the most popular search engine for full-text database management systems. By default, its configuration does not change while it receives data. However, when Elasticsearch stores a large amount of data over time, the defaul
Externí odkaz:
https://doaj.org/article/f669845c7f744bae9cc8021ad4b605f6