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Machine Learning: Algorithms, Real-World Applications and Research
To discuss the applicability of machine learning-based solutions in various real-world application domains. To highlight and summarize the potential research directions within the scope of our study for intelligent data analysis and services. The rest of the paper is organized as follows.
PDF Machine Learning: Algorithms, Real-World Applications and Research
Types of Real‐World Data and Machine Learning Techniques. Machine learning algorithms typically consume and process data to learn the related patterns about individuals, business processes, transactions, events, and so on. In the following, we discuss various types of real-world data as well as cat-egories of machine learning algorithms.
(PDF) Research on Machine Learning and Its Algorithms and Development
It combines analysis on common algorithms in machine learning, such as decision tree algorithm, random forest algorithm, artificial neural network algorithm, SVM algorithm, Boosting and Bagging ...
Machine Learning: Algorithms, Real-World Applications and Research
The learning algorithms can be categorized into four major types, such as supervised, unsupervised, semi-supervised, and reinforcement learning in the area [ 75 ], discussed briefly in Sect. " Types of Real-World Data and Machine Learning Techniques ". The popularity of these approaches to learning is increasing day-by-day, which is shown ...
Machine Learning
Additional hard and PDF copies can be obtained from [email protected] Machine Learning - Algorithms, Models and Applications Edited by Jaydip Sen p. cm. This title is part of the Artificial Intelligence Book Series, Volume 7 Topic: Machine Learning and Data Mining Series Editor: Andries Engelbrecht Topic Editor: Marco Antonio Aceves Fernandez
[2104.05314] Machine learning and deep learning
Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of analytical model building and solve associated tasks. Deep learning is a machine learning concept based on artificial neural networks. For many applications, deep ...
Journal of Machine Learning Research
(Machine Learning Open Source Software Paper) TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads Paweł Rościszewski, Michał Martyniak, Filip Schodowski; (215):1−5, 2021. (Machine Learning Open Source Software Paper)
PDF Machine Learning Model Development from a Software Engineering
arXiv:2102.07574v1 [cs.SE] 15 Feb 2021 Machine Learning Model Development from a Software Engineering Perspective: A Systematic Literature Review Giuliano Lorenzoni David R. Cheriton School of Computer Science ... research papers in search of methods for testing and debugging the ML code. Theirfindings show that onlya few contributions focus ...
Proceedings of Machine Learning Research
Proceedings of the 38th International Conference on Machine Learning Held in Virtual on 18-24 July 2021 Published as Volume 139 by the Proceedings of Machine Learning Research on 01 July 2021. Volume Edited by: Marina Meila Tong Zhang Series Editors: Neil D. Lawrence
PDF An industry perspective on machine learning
An industry perspective on machine learning. Google Applied Science is a division of Google Research that applies computational methods, and in particular machine learning, to a broad range of ...
JMLR Papers
JMLR Papers. Select a volume number to see its table of contents with links to the papers. Volume 23 (January 2022 - Present) . Volume 22 (January 2021 - December 2021) . Volume 21 (January 2020 - December 2020) . Volume 20 (January 2019 - December 2019) . Volume 19 (August 2018 - December 2018) . Volume 18 (February 2017 - August 2018) . Volume 17 (January 2016 - January 2017)
Machine learning-based approach: global trends, research directions
Artificial intelligence (AI), and in particular, Machine Learning (ML), have progressed remarkably in recent years as key instruments to intelligently analyze such data and to develop the corresponding real-world applications (Koteluk et al., 2021; Sarker, 2021b).For instance, ML has emerged as the method of choice for developing practical software for computer vision, speech recognition, and ...
PDF Review of Artificial Intelligence and Machine Learning Technologies
increased interest in research in this area. It can be illustrated by the number of publications in scientific databases. The graph presented in Figure1shows the number of reviews in AI, ML, and DL in Scopus in years 2000-2021. Figure 1. The number of review studies devoted to artificial intelligence (AI), machine learning (ML),
PDF Machine Learning Cybersecurity Adoption in Small and Medium Enterprises
As seen in Figure 1 above, this paper invest igates advanced research on the issues of cybersecurity within the SME market in developed nations using machine learning and combining the strength of machine learning and cybersecurity (MLCS). This paper goes on to focus on the awareness of MLCS, leading to barriers and challenges to the adoption
Journal of Machine Learning Research
The Journal of Machine Learning Research (JMLR), , provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online. JMLR has a commitment to rigorous yet rapid reviewing. Final versions are (ISSN 1533-7928) immediately ...
PDF Security and privacy in machine learning: A survey
and decisive solution. Machine learning model is used for classifying the data with at the most accuracy. Various kinds of machine learning algorithms and techniques are available. However, the latest research studies show that machine learning using data could be vulnerable to security attacks, malware detection, and many more.
Top 10 Machine Learning Research Papers of 2021
Machine learning research papers showcasing the transformation of the technology In 2021, machine learning and deep learning had many amazing advances and important research papers may lead to breakthroughs in technology that get used by billions of people. The research in this field is developing very quickly and to help you monitor the progress here is the list of most important recent ...
machine learning Latest Research Papers
10.1016/j.istruc.2021.12. ... This article examines the background to the problem and outlines a project that TNA undertook to research the feasibility of using commercially available artificial intelligence tools to aid selection. ... this research aims to predict user's personalities based on Indonesian text from social media using machine ...
PDF Machine Learning Technologies for Big Data Analytics
published papers, which can help future researchers easily find starting points in their research in the domain of machine learning for big data analytics problems. It would be intriguing to expand the research to other organs such as the liver, lungs, and other multi-modal medical imaging modalities in the future. A new deep CNN model can be ...
PDF Keywords: Industrial Applications of Machine Learning, Explainable
Enhancing Manufacturing Quality Prediction Models through the Integration of Explainability Methods Dennis Gross 1, Helge Spieker , Arnaud Gotlieb , and Ricardo Knoblauch2 1Simula Research Laboratory, Oslo, Norway 2Ecole Nationale Sup´erieure d'Arts et M ´etiers, Aix-en-Provence, France [email protected] Keywords: Industrial Applications of Machine Learning, Explainable Machine Learning
Predicting and improving complex beer flavor through machine learning
Abstract. The perception and appreciation of food flavor depends on many interacting chemical compounds and external factors, and therefore proves challenging to understand and predict. Here, we ...
Machine Learning
In machine learning, a computer first learns to perform a task by studying a training set of examples. The computer then performs the same task with data it hasn't encountered before. This article presents a brief overview of machine-learning technologies, with a concrete case study from code analysis.
JMLR Papers
JMLR Papers. Select a volume number to see its table of contents with links to the papers. Volume 25 (January 2024 - Present) . Volume 24 (January 2023 - December 2023) . Volume 23 (January 2022 - December 2022) . Volume 22 (January 2021 - December 2021) . Volume 21 (January 2020 - December 2020) . Volume 20 (January 2019 - December 2019) ...
NeurIPS 2024
The Neural Information Processing Systems Foundation is a non-profit corporation whose purpose is to foster the exchange of research advances in Artificial Intelligence and Machine Learning, principally by hosting an annual interdisciplinary academic conference with the highest ethical standards for a diverse and inclusive community.
[2403.20208v1] Unleashing the Potential of Large Language Models for
View PDF Abstract: In the domain of data science, the predictive tasks of classification, regression, and imputation of missing values are commonly encountered challenges associated with tabular data. This research endeavors to apply Large Language Models (LLMs) towards addressing these predictive tasks. Despite their proficiency in comprehending natural language, LLMs fall short in dealing ...
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COMMENTS
To discuss the applicability of machine learning-based solutions in various real-world application domains. To highlight and summarize the potential research directions within the scope of our study for intelligent data analysis and services. The rest of the paper is organized as follows.
Types of Real‐World Data and Machine Learning Techniques. Machine learning algorithms typically consume and process data to learn the related patterns about individuals, business processes, transactions, events, and so on. In the following, we discuss various types of real-world data as well as cat-egories of machine learning algorithms.
It combines analysis on common algorithms in machine learning, such as decision tree algorithm, random forest algorithm, artificial neural network algorithm, SVM algorithm, Boosting and Bagging ...
The learning algorithms can be categorized into four major types, such as supervised, unsupervised, semi-supervised, and reinforcement learning in the area [ 75 ], discussed briefly in Sect. " Types of Real-World Data and Machine Learning Techniques ". The popularity of these approaches to learning is increasing day-by-day, which is shown ...
Additional hard and PDF copies can be obtained from [email protected] Machine Learning - Algorithms, Models and Applications Edited by Jaydip Sen p. cm. This title is part of the Artificial Intelligence Book Series, Volume 7 Topic: Machine Learning and Data Mining Series Editor: Andries Engelbrecht Topic Editor: Marco Antonio Aceves Fernandez
Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of analytical model building and solve associated tasks. Deep learning is a machine learning concept based on artificial neural networks. For many applications, deep ...
(Machine Learning Open Source Software Paper) TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads Paweł Rościszewski, Michał Martyniak, Filip Schodowski; (215):1−5, 2021. (Machine Learning Open Source Software Paper)
arXiv:2102.07574v1 [cs.SE] 15 Feb 2021 Machine Learning Model Development from a Software Engineering Perspective: A Systematic Literature Review Giuliano Lorenzoni David R. Cheriton School of Computer Science ... research papers in search of methods for testing and debugging the ML code. Theirfindings show that onlya few contributions focus ...
Proceedings of the 38th International Conference on Machine Learning Held in Virtual on 18-24 July 2021 Published as Volume 139 by the Proceedings of Machine Learning Research on 01 July 2021. Volume Edited by: Marina Meila Tong Zhang Series Editors: Neil D. Lawrence
An industry perspective on machine learning. Google Applied Science is a division of Google Research that applies computational methods, and in particular machine learning, to a broad range of ...
JMLR Papers. Select a volume number to see its table of contents with links to the papers. Volume 23 (January 2022 - Present) . Volume 22 (January 2021 - December 2021) . Volume 21 (January 2020 - December 2020) . Volume 20 (January 2019 - December 2019) . Volume 19 (August 2018 - December 2018) . Volume 18 (February 2017 - August 2018) . Volume 17 (January 2016 - January 2017)
Artificial intelligence (AI), and in particular, Machine Learning (ML), have progressed remarkably in recent years as key instruments to intelligently analyze such data and to develop the corresponding real-world applications (Koteluk et al., 2021; Sarker, 2021b).For instance, ML has emerged as the method of choice for developing practical software for computer vision, speech recognition, and ...
increased interest in research in this area. It can be illustrated by the number of publications in scientific databases. The graph presented in Figure1shows the number of reviews in AI, ML, and DL in Scopus in years 2000-2021. Figure 1. The number of review studies devoted to artificial intelligence (AI), machine learning (ML),
As seen in Figure 1 above, this paper invest igates advanced research on the issues of cybersecurity within the SME market in developed nations using machine learning and combining the strength of machine learning and cybersecurity (MLCS). This paper goes on to focus on the awareness of MLCS, leading to barriers and challenges to the adoption
The Journal of Machine Learning Research (JMLR), , provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online. JMLR has a commitment to rigorous yet rapid reviewing. Final versions are (ISSN 1533-7928) immediately ...
and decisive solution. Machine learning model is used for classifying the data with at the most accuracy. Various kinds of machine learning algorithms and techniques are available. However, the latest research studies show that machine learning using data could be vulnerable to security attacks, malware detection, and many more.
Machine learning research papers showcasing the transformation of the technology In 2021, machine learning and deep learning had many amazing advances and important research papers may lead to breakthroughs in technology that get used by billions of people. The research in this field is developing very quickly and to help you monitor the progress here is the list of most important recent ...
10.1016/j.istruc.2021.12. ... This article examines the background to the problem and outlines a project that TNA undertook to research the feasibility of using commercially available artificial intelligence tools to aid selection. ... this research aims to predict user's personalities based on Indonesian text from social media using machine ...
published papers, which can help future researchers easily find starting points in their research in the domain of machine learning for big data analytics problems. It would be intriguing to expand the research to other organs such as the liver, lungs, and other multi-modal medical imaging modalities in the future. A new deep CNN model can be ...
Enhancing Manufacturing Quality Prediction Models through the Integration of Explainability Methods Dennis Gross 1, Helge Spieker , Arnaud Gotlieb , and Ricardo Knoblauch2 1Simula Research Laboratory, Oslo, Norway 2Ecole Nationale Sup´erieure d'Arts et M ´etiers, Aix-en-Provence, France [email protected] Keywords: Industrial Applications of Machine Learning, Explainable Machine Learning
Abstract. The perception and appreciation of food flavor depends on many interacting chemical compounds and external factors, and therefore proves challenging to understand and predict. Here, we ...
In machine learning, a computer first learns to perform a task by studying a training set of examples. The computer then performs the same task with data it hasn't encountered before. This article presents a brief overview of machine-learning technologies, with a concrete case study from code analysis.
JMLR Papers. Select a volume number to see its table of contents with links to the papers. Volume 25 (January 2024 - Present) . Volume 24 (January 2023 - December 2023) . Volume 23 (January 2022 - December 2022) . Volume 22 (January 2021 - December 2021) . Volume 21 (January 2020 - December 2020) . Volume 20 (January 2019 - December 2019) ...
The Neural Information Processing Systems Foundation is a non-profit corporation whose purpose is to foster the exchange of research advances in Artificial Intelligence and Machine Learning, principally by hosting an annual interdisciplinary academic conference with the highest ethical standards for a diverse and inclusive community.
View PDF Abstract: In the domain of data science, the predictive tasks of classification, regression, and imputation of missing values are commonly encountered challenges associated with tabular data. This research endeavors to apply Large Language Models (LLMs) towards addressing these predictive tasks. Despite their proficiency in comprehending natural language, LLMs fall short in dealing ...