Results 41 to 50 of about 1,424,164 (189)
DEVELOPMENT OF R PACKAGE AND EXPERIMENTAL ANALYSIS ON PREDICTION OF THE CO2 COMPRESSIBILITY FACTOR USING GRADIENT DESCENT [PDF]
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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On the Generalization of Stochastic Gradient Descent with Momentum
This entry is redundant and was created in error.
Ramezani-Kebrya, Ali +2 more
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Design of Momentum Fractional Stochastic Gradient Descent for Recommender Systems
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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Efficiency Ordering of Stochastic Gradient Descent
To appear in NeurIPS ...
Jie Hu 0027 +2 more
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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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Damped Newton Stochastic Gradient Descent Method for Neural Networks Training
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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Perbandingan Teknik Klasifikasi Dalam Data Mining Untuk Bank Direct Marketing
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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Normalized stochastic gradient descent learning of general complex‐valued models
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 Fixed-Point of View on Gradient Methods for Big Data
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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Counterexamples for Noise Models of Stochastic Gradients
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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