Results 31 to 40 of about 142,362 (315)
Improving Convergence in Therapy Scheduling Optimization: A Simulation Study
Mathematics, 2020 The infusion times and drug quantities are two primary variables to optimize when designing a therapeutic schedule. In this work, we test and analyze several extensions to the gradient descent equations in an optimal control algorithm conceived for ...
Juan C. Chimal-Eguia +2 more
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The Improved Stochastic Fractional Order Gradient Descent Algorithm
Fractal and Fractional, 2023 This paper mainly proposes some improved stochastic gradient descent (SGD) algorithms with a fractional order gradient for the online optimization problem.
Yang Yang, Lipo Mo, Yusen Hu, Fei Long
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Scaling transition from momentum stochastic gradient descent to plain stochastic gradient descent
, 2021 The plain stochastic gradient descent and momentum stochastic gradient descent have extremely wide applications in deep learning due to their simple settings and low computational complexity. The momentum stochastic gradient descent uses the accumulated gradient as the updated direction of the current parameters, which has a faster training speed ...
Zeng, Kun +3 more
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Correspondence between neuroevolution and gradient descent
Nature Communications, 2021 Gradient-based and non-gradient-based methods for training neural networks are usually considered to be fundamentally different. The authors derive, and illustrate numerically, an analytic equivalence between the dynamics of neural network training under
Stephen Whitelam +3 more
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Jurnal Elkomika, 2022 ABSTRAK Terdapat banyak variable nonlinear dalam sistem kendali untuk quadcopter sehingga cukup rumit untuk mengatur dinamika penerbangan wahana ini. Untuk mengatasi masalah tersebut akan dikembangkan suatu skema sistem kendali Direct Inverse Control ...
MUHAMMAD SABILA HAQQI +1 more
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Design of Momentum Fractional Stochastic Gradient Descent for Recommender Systems
IEEE Access, 2019 The demand for recommender systems in E-commerce industry has increased tremendously. Efficient recommender systems are being proposed by different E-business companies with the intention to give users accurate and most relevant recommendation of ...
Zeshan Aslam Khan +4 more
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Normalized stochastic gradient descent learning of general complex‐valued models
Electronics Letters, 2021 The stochastic gradient descent (SGD) method is one of the most prominent first‐order iterative optimisation algorithms, enabling linear adaptive filters as well as general nonlinear learning schemes.
T. Paireder, C. Motz, M. Huemer
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A Synchronized Gradient Descent Algorithm Based on Distributed Coding [PDF]
Jisuanji gongcheng, 2021 The Asynchronized Stochastic Gradient Descent(ASGD) algorithm based on data parallelization require frequent gradient data exchanges between distributed computing nodes,which affects the execution efficiency of the algorithm.This paper proposes a ...
LI Bowen, XIE Zaipeng, MAO Yingchi, XU Yuanyuan, ZHU Xiaorui, ZHANG Ji
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Stochastic gradient descent on GPUs [PDF]
Proceedings of the 8th Workshop on General Purpose Processing using GPUs, 2015 Irregular algorithms such as Stochastic Gradient Descent (SGD) can benefit from the massive parallelism available on GPUs. However, unlike in data-parallel algorithms, synchronization patterns in SGD are quite complex. Furthermore, scheduling for scale-free graphs is challenging.
Rashid Kaleem +2 more
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DEVELOPMENT OF R PACKAGE AND EXPERIMENTAL ANALYSIS ON PREDICTION OF THE CO2 COMPRESSIBILITY FACTOR USING GRADIENT DESCENT [PDF]
Journal of Engineering Science and Technology, 2018 Nowadays, many variants of gradient descent (i.e., the methods included in machine learning for regression) have been proposed. Moreover, these algorithms have been widely used to deal with real-world problems.
LALA SEPTEM RIZA +5 more
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