359.866 hasil untuk machine learning
Menampilkan 421–440 · 0,60 detik · RSS
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Artikel Jurnal
Machine learning the deuteron
We use machine learning techniques to solve the nuclear two-body bound state problem, the deuteron. We use a minimal one-layer, feed-forward neural network to represent the deuteron S- and D-state wavefunction in momentum space, and solve the problem variationally using ready-made machine learning…
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Artikel Jurnal
Self-directed machine learning
Conventional machine learning (ML) relies heavily on manual design from machine learning experts to decide learning tasks, data, models, optimization algorithms, and evaluation metrics, which is labor-intensive, time-consuming, and cannot learn autonomously like humans. In education science…
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Artikel Jurnal
Diversity in Machine Learning
Machine learning methods have achieved good performance and been widely applied in various real-world applications. They can learn the model adaptively and be better fit for special requirements of different tasks. Generally, a good machine learning system is composed of plentiful training data, a…
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Artikel Jurnal
Copying Machine Learning Classifiers
We study copying of machine learning classifiers, an agnostic technique to replicate the decision behavior of any classifier. We develop the theory behind the problem of copying, highlighting its properties, and propose a framework to copy the decision behavior of any classifier using no prior…
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Artikel Jurnal
Machine learning for combustion
…to improve the combustion efficiency with minimum emission of pollutants. Machine learning facilitates data-driven techniques for handling large amounts of combustion data, either obtained through experiments or simulations under multiple spatiotemporal scales, thereby finding the hidden patterns…
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Artikel Jurnal
Machine learning for semiconductors
…and the development of semicondulctor manufacturing. Fortunately, machine learning, as a fast-growing tool from computer science, is expected to significantly speed up the data analysis. In recently years, many researches on machine learning study of semiconductor materials and semiconductor…
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Artikel Jurnal Teks lengkap
Machine Learning for Communications
Due to the proliferation of applications and services that run over communication networks, ranging from video streaming and data analytics to robotics and augmented reality, tomorrow’s networks will be faced with increasing challenges resulting from the explosive growth of data traffic demand with…
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Artikel Jurnal
Machine learning in epidemiology
In this paper, we conduct a study based on machine learning tools to identify risk factors related to the occurrence of both forms of tuberculosis (noted "TB"). To do so, we use data collected from the registries of the Settat Center for Diagnosis of TB and Respiratory Diseases (CDTMR). As analysis…
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Artikel Jurnal
Machine-learning media bias.
We present an automated method for measuring media bias. Inferring which newspaper published a given article, based only on the frequencies with which it uses different phrases, leads to a conditional probability distribution whose analysis lets us automatically map newspapers and phrases into a…
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Artikel Jurnal
Machine learning portfolio allocation
We find economically and statistically significant gains when using machine learning for portfolio allocation between the market index and risk-free asset. Optimal portfolio rules for time-varying expected returns and volatility are implemented with two Random Forest models. One model is employed…
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Artikel Jurnal
Quantum adversarial machine learning
Adversarial machine learning is an emerging field that focuses on studying vulnerabilities of machine learning approaches in adversarial settings and developing techniques accordingly to make learning robust to adversarial manipulations. It plays a vital role in various machine learning…
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Artikel Jurnal Teks lengkap
Machine Learning in KM3NeT
…(ARCA) and of determining the neutrino mass hierarchy (ORCA). Various Machine Learning techniques, such as Random Forests, BDTs, Shallow and Deep Networks are being used for diverse tasks, such as event-type and particle identification, energy/direction estimation, source identification…
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Artikel Jurnal
Machine learning and essentialism
Machine learning and essentialism have been connected in the past by various researchers, in order to state that the main paradigm in machine learning processes is equivalent to choosing the “essential” attributes for the machine to search for. Our goal in this paper is to show that there are…
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Artikel Jurnal
Machine learning CICY threefolds
…the paradigm that classes of problems in algebraic geometry can be machine learned. Keywords: Machine learning, Neural network, Support Vector Machine, Calabi–Yau, String compactifications
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Artikel Jurnal
Machine learning powered ellipsometry
…but also limit the applicability of ellipsometry. Here, we demonstrate a machine learning based approach for solving ellipsometric problems in an unambiguous and fully automatic manner while showing superior performance. The proposed approach is experimentally validated by using a broad range of…
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