204.674 hasil untuk machine learning
Menampilkan 661–680 · 0,93 detik · RSS
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Artikel Jurnal
Small data machine learning in materials science
Abstract This review discussed the dilemma of small data faced by materials machine learning. First, we analyzed the limitations brought by small data. Then, the workflow of materials machine learning has been introduced. Next, the methods of dealing with small data were introduced, including data…
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Machine Learning with Squared-Loss Mutual Information
Mutual information (MI) is useful for detecting statistical independence between random variables, and it has been successfully applied to solving various machine learning problems. Recently, an alternative to MI called squared-loss MI (SMI) was introduced. While ordinary MI is the…
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Visibility Prediction Based on Machine Learning Algorithms
In this study, ground observation data were selected from January 2016 to January 2020. First, six machine learning methods were used to predict visibility. We verified the accuracy of the method with and without principal components analysis (PCA) by combining actual examples with the European…
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Encrypted machine learning of molecular quantum properties
Large machine learning (ML) models with improved predictions have become widely available in the chemical sciences. Unfortunately, these models do not protect the privacy necessary within commercial settings, prohibiting the use of potentially extremely valuable data by others. Encrypting the…
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An Empirical Review of Automated Machine Learning
In recent years, Automated Machine Learning (AutoML) has become increasingly important in Computer Science due to the valuable potential it offers. This is testified by the high number of works published in the academic field and the significant efforts made in the industrial sector. However, some…
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Artikel Jurnal
Machine Learning‐Enabled Noncontact Sleep Structure Prediction
…are extracted. The performance of the NSSPS is validated by transfer learning between radar signals with different frequency bands and crossvalidation among different subjects. Moreover, the NSSPS is demonstrated to estimate overnight parameters that are critical for sleep diagnosis. Benefiting…
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Artikel Jurnal
Machine learning algorithm application in trip planning
This article explores how machine learning can be applied in efficiently solving a variation of the Travelling Salesman Problem (TSP) in the context of air travel tourism. Large number of cities create too many trip route combinations to be efficiently evaluated in real time. The method proposed…
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Machine learning assisted quantum super-resolution microscopy
…time-consuming acquisition of multi-photon event histograms. We present a machine learning-assisted approach for the realization of rapid antibunching super-resolution imaging and demonstrate 12 times speed-up compared to conventional, fitting-based autocorrelation measurements. The developed…
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Artikel Jurnal
Recruitment in the Times of Machine Learning
How do socio-economic change and technological revolution change the way we manage people. How does the development of AI (Artificial Intelligence) affect the process of talent acquisition? The author will present the concepts of technological unemployment, creative class, millennials (generation…
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New Results on Machine Learning-Based Distinguishers
Machine Learning (ML) is almost ubiquitously used in multiple disciplines nowadays. Recently, we have seen its usage in the realm of differential distinguishers for symmetric key ciphers. It has been shown that ML-based differential distinguishers can be easily extended to break round-reduced…
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Machine learning for microalgae detection and utilization
…to identify microalgae species and monitor microalgae changes. Machine learning techniques have achieved massive success in object recognition and classification, and have attracted a wide range of attention. Many researchers have introduced machine learning algorithms into microalgae applications…
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Machine Learning-Based Prediction of Air Quality
…collected by Taiwan’s Environmental Protection Administration (EPA). Machine learning methods, including adaptive boosting (AdaBoost), artificial neural network (ANN), random forest, stacking ensemble, and support vector machine (SVM), produce promising results for air quality index (AQI) level…
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Coding for Large-Scale Distributed Machine Learning
This article aims to give a comprehensive and rigorous review of the principles and recent development of coding for large-scale distributed machine learning (DML). With increasing data volumes and the pervasive deployment of sensors and computing machines, machine learning has become more…
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Detecting Suspicious Texts Using Machine Learning Techniques
…suspicious text efficiently from the specific contents. In this paper, a Machine Learning (ML)-based classification model is proposed (hereafter called STD) to classify Bengali text into non-suspicious and suspicious categories based on its original contents. A set of ML classifiers with various…
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Machine Learning in Tribology—More than Buzzwords?
Tribology has been and continues to be one of the most relevant fields, being present in almost all aspects of our lives [...]
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Bacterial Immunogenicity Prediction by Machine Learning Methods
The identification of protective immunogens is the most important and vigorous initial step in the long-lasting and expensive process of vaccine design and development. Machine learning (ML) methods are very effective in data mining and in the analysis of big data such as microbial proteomes. They…
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Classification of Malicious URLs Using Machine Learning
…could be compromised. This study aims to develop models based on machine learning algorithms for the efficient identification and classification of malicious URLs, contributing to enhanced cybersecurity. Within this context, this study leverages support vector machines (SVMs), random forests (RFs)…
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IoT Device Identification Using Unsupervised Machine Learning
…such as traffic patterns which could be used for device identification. Machine-learning-assisted approaches are promising for device identification since they can capture dynamic device behaviors and have automation capabilities. Supervised machine-learning-assisted techniques demonstrate high…
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