204.674 hasil untuk machine learning
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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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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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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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Artikel Jurnal Teks lengkap
Machine Learning in Education
This narrative review examines the historical evolution, current applications, and major challenges of machine learning (ML) in education, positioning ML as a transformative yet deeply contested force in contemporary teaching and learning. Tracing developments from early computer-assisted…
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Artikel Jurnal
Machine learning electroweakino production
…\nu {\bar{\nu }}$$ Z → ν ν ¯ ) background. In this study, we explore Machine Learning (ML) methods for efficient signal/background discrimination. Our best attempt uses both reconstructed (jets, missing transverse energy, etc.) and low-level (particle-flow) objects. We find that the discrimination…
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Machine Learning in Bioelectrocatalysis
…experimental conditions. These issues can possibly be solved using machine learning (ML) in recent reports although the combination of them is still not mature. To summarize the progress of ML in bioelectrocatalysis, this paper first introduces the modeling process of ML, then focuses on the…
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Artikel Jurnal
Weakly supervised machine learning
Abstract Supervised learning aims to build a function or model that seeks as many mappings as possible between the training data and outputs, where each training data will predict as a label to match its corresponding ground‐truth value. Although supervised learning has achieved great success in…
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Artikel Jurnal Teks lengkap
Federated Quantum Machine Learning
…One of the potential schemes to achieve this property is the federated learning (FL), which consists of several clients or local nodes learning on their own data and a central node to aggregate the models collected from those local nodes. However, to the best of our knowledge, no work has been done…
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