Results 31 to 40 of about 23,797 (211)
Adaptive Gradient Estimation Stochastic Parallel Gradient Descent Algorithm for Laser Beam Cleanup
Photonics, 2021 For a high-power slab solid-state laser, obtaining high output power and high output beam quality are the most important indicators. Adaptive optics systems can significantly improve beam qualities by compensating for the phase distortions of the laser ...
Shiqing Ma +8 more
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Edumatic, 2020 Kopi Arabika merupakan salah satu minuman favorit bagi banyak orang. Dalam pembuatannya, kopi arabika memiliki takaran yang berbeda disetiap negara, yang menghasilkan kualitas yang berbeda pula. Penelitian kopi arabika ini menggunakan dataset yang berisi
Veronica Retno Sari +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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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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Damped Newton Stochastic Gradient Descent Method for Neural Networks Training
Mathematics, 2021 First-order methods such as stochastic gradient descent (SGD) have recently become popular optimization methods to train deep neural networks (DNNs) for good generalization; however, they need a long training time.
Jingcheng Zhou +3 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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Perbandingan Teknik Klasifikasi Dalam Data Mining Untuk Bank Direct Marketing
Jurnal Teknologi Informasi dan Ilmu Komputer, 2018 Klasifikasi merupakan teknik dalam data mining untuk mengelompokkan data berdasarkan keterikatan data terhadap data sampel. Pada penelitian ini, kami melakukan perbandingan 9 teknik klasifikasi untuk mengklasifikasi respon pelanggan pada dataset Bank ...
Irvi Oktanisa, Ahmad Afif Supianto
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Counterexamples for Noise Models of Stochastic Gradients
Examples and Counterexamples, 2023 Stochastic Gradient Descent (SGD) is a widely used, foundational algorithm in data science and machine learning. As a result, analyses of SGD abound making use of a variety of assumptions, especially on the noise behavior of the stochastic gradients ...
Vivak Patel
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A Fixed-Point of View on Gradient Methods for Big Data
Frontiers in Applied Mathematics and Statistics, 2017 Interpreting gradient methods as fixed-point iterations, we provide a detailed analysis of those methods for minimizing convex objective functions. Due to their conceptual and algorithmic simplicity, gradient methods are widely used in machine learning ...
Alexander Jung
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