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Understanding machine translation fit for language learning: The mediating effect of machine translation literacy
The use of machine translation has become a topic of debate in language learning, which highlights the need to thoroughly examine the appropriateness...
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Research trends in deep learning and machine learning for cloud computing security
Deep learning and machine learning show effectiveness in identifying and addressing cloud security threats. Despite the large number of articles...
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Confidentiality of Machine Learning Models
AbstractThis article is about ensuring the confidentiality of models using machine learning systems. The aim of this study is to ensure the...
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Comparative Analysis of Machine Learning, Ensemble Learning and Deep Learning Classifiers for Parkinson’s Disease Detection
A progressive neurodegenerative ailment called Parkinson's disease (PD) is marked by the death of dopamine-producing cells in the substantia nigra...
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Application of machine learning and deep learning for cancer vaccine (rapid review)
Cancer is a common and dangerous disease based on the World Health Organization. Much research has been done on new and effective cancer treatments,...
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Blockchain meets machine learning: a survey
Blockchain and machine learning are two rapidly growing technologies that are increasingly being used in various industries. Blockchain technology...
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Machine learning with a reject option: a survey
Machine learning models always make a prediction, even when it is likely to be inaccurate. This behavior should be avoided in many decision support...
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Machine learning and non-machine learning methods in mathematical recognition systems: Two decades’ systematic literature review
Tools based on machine learning (ML) have seen widespread application in the prediction and categorization of mathematical symbols and phrases. The...
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Diabetes detection based on machine learning and deep learning approaches
The increasing number of diabetes individuals in the globe has alarmed the medical sector to seek alternatives to improve their medical technologies....
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Automated machine learning: past, present and future
Automated machine learning (AutoML) is a young research area aiming at making high-performance machine learning techniques accessible to a broad set...
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Adversarial learning with optimism for bias reduction in machine learning
Recently, machine learning has gained enormous momentum and been extensively applied to decision making. However, biases in machine learning models...
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Protection of Computational Machine Learning Models against Extraction Threat
AbstractThe extraction threat to machine learning models is considered. Most contemporary methods of defense against the extraction of computational...
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Machine Learning for All!—Introducing Machine Learning in Middle and High School
Although Machine Learning (ML) is found practically everywhere, few understand the technology behind it. This presents new challenges to extend...
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Machine Learning for Multiscale Video Coding
AbstractThe research concerns the use of machine learning algorithms for multiscale coding of digital video sequences. Based on machine learning, the...
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Optimized machine learning model discourse analysis
In recent years, online education has been given more and more attention with the widespread use of the internet. The teaching procedure divides...
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Machine-learning abstractions for component-based self-optimizing systems
This paper features an approach that combines machine-learning abstractions with a component model. We target modern self-optimizing systems and...
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Robust machine learning models: linear and nonlinear
Artificial Intelligence relies on the application of machine learning models which, while reaching high predictive accuracy, lack explainability and...
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Machine learning and deep learning techniques for poultry tasks management: a review
In recent years the poultry production industry has adopted automation with the help of different kinds of technological advancements like verities...
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How good are machine learning clouds? Benchmarking two snapshots over 5 years
We conduct an empirical study of machine learning functionalities provided by major cloud service providers, which we call machine learning clouds ....
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Machine learning and human learning: a socio-cultural and -material perspective on their relationship and the implications for researching working and learning
The paper adopts an inter-theoretical socio-cultural and -material perspective on the relationship between human + machine learning to propose a new...