Machine Learning. Abstract: 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.
Machine learning and its applications: A review
Nowadays, large amount of data is available everywhere. Therefore, it is very important to analyze this data in order to extract some useful information and to develop an algorithm based on this analysis. This can be achieved through data mining and machine learning. Machine learning is an integral part of artificial intelligence, which is used to design algorithms based on the data trends and ...
Research on machine learning algorithms and feature ...
This paper aims to use various machine learning algorithms and explore the influence between different algorithms and multi-feature in the time series. The real consumption records constitute the time series as the research object. We extract consumption mark, frequency and other features. Moreover, we utilize support vector machine (SVM), long short-term memory (LSTM) and other algorithms to ...
IEEE
Abstract— In this paper, a novel system architecture including a massive multi-input multi-output (MIMO) or a reconfigurable intelligent surface (RIS) and multiple autonomous vehicles is considered in vehicle location systems. Autonomous Vehicles Super-Resolution. Paper. Add Code.
Code Generation Using Machine Learning: A Systematic Review
This review provides a broad and detailed overview of studies for code generation using ML. We selected 37 publications indexed in arXiv and IEEE Xplore databases that train ML models on programming language data to generate code. The three paradigms of code generation we identified in these studies are description-to-code, code-to-description ...
Proceedings of the IEEE
Computational Media Intelligence: Human-Centered Machine Analysis of Media. By K. Somandepalli, T. Guha, V. R. Martinez, N. Kumar, H. Adam, and S. Narayanan. The topic treated in this article is the application of deep learning algorithms, combined with audio-visual signal processing, to analyze entertainment media such as film/TV.
machine learning Archives
In this paper, an intelligent identification method for rail vehicle running state is proposed based on Tiny Machine Learning (TinyML) technology, and an IoT system is developed with small size and low energy consumption. The system uses a Micro-Electro-Mechanical System (MEMS) sensor to collect acceleration data for machine learning training.
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.
Ieee Transactions on Neural Networks and Learning Systems, Vol. Xx, No
research in the field. Index Terms—deep learning, neural networks, natural lan-guage processing, computational linguistics, machine learning I. INTRODUCTION T HE field of natural language processing (NLP) encom-passes a variety of topics which involve the compu-tational processing and understanding of human languages.
s social systems, ecosystems, biological networks, knowledge graphs, and information systems. With the continuous penetra-tion of artificial intelligence technologies, graph learning (i. e., machine learning on graphs) is gaining attention from both researchers and practitioners. Graph le. rning proves effective for many tasks, such as ...
Image Processing Technology Based on Machine Learning
Machine learning is a relatively new field. With the deepening of people's research in this field, the application of machine learning is increasingly extensive. On the other hand, with the advancement of science and technology, graphics have been an indispensable medium of information transmission, and image processing technology is also booming. However, the traditional image processing ...
IEEE Transactions on Machine Learning in Communications and Networking
IEEE TMLCN also particularly encourages the submission of papers that simultaneously advance both the fields of machine learning and wireless networking. The journal also advocates for reproducible and public sharing of codes, datasets, software, and other artefacts related to research contributions.
Machine Learning on IEEE Technology Navigator
Comparison of Classification Techniques used in **Machine Learning** as Applied on Vocational Guidance Data. Traffic Prediction for Intelligent Transportation System using **Machine Learning**. Audio, Speech, and Language Processing, IEEE Transactions on. Automatic Control, IEEE Transactions on.
Proceedings of the IEEE
Efficient Acceleration of Deep Learning Inference on Resource-Constrained Edge Devices: A Review. By M. M. Hossain Shuvo, S. K. Islam, J. Cheng, and B. I. Morshed. This article provides a comprehensive review of the state-of-the-art tools and techniques for efficient edge inference, a vital element of artificial intelligence on edge.
IEEE Access Special Section Editorial: Machine Learning Designs
Most modern machine learning research is devoted to improving the accuracy of prediction. However, less attention is paid to the deployment of the machine and deep learning systems, supervised ...
An Overview on Application of Machine Learning Techniques in Optical
discusses some possible open areas of research and future directions, whereas Section VIII concludes the paper. II. OVERVIEW OF MACHINE LEARNING METHODS USED IN OPTICAL NETWORKS This section provides an overview of some of the most popular algorithms that are commonly classified as machine learning. The literature on ML is so extensive that even a
Machine Learning Faces a Reckoning in Health Research
Two new analyses put the spotlight on machine learning in health research, where lack of reproducibility and poor quality is especially alarming. "If a doctor is using machine learning or an ...
INGR Roadmap Artificial Intelligence And Machine Learning ...
Abstract: In the evolution of artificial Intelligence (AI) and machine learning (ML), reasoning, knowledge representation, planning, learning, natural language processing, perception, and the ability to move and manipulate objects have been widely used. These features enable the creation of intelligent mechanisms for decision support to overcome the limits of human knowledge processing.
Machine Learning
Moroccan Dialect Emotion Recognition Dataset. Moroccan Dialect Emotion Recognition Dataset is a collection of voice records of people speaking Moroccan dialect in 5 states of emotion: Neutral, Happy, Sad, Angry and Fearful. The dataset has been collected in different Moroccan cities in 2024. Each recorder has 5 records per emotion class.
PDF Artificial Intelligence and Machine Learning Applied to ...
The opportunity, nearly a necessity, is for security artificial intelligence (AI)/machine learning (ML) to act as a force multiplier by augmenting the cybersecurity workforce's ability to defend at scale and speed. The agility created by AI/ML augmentation of a cybersecurity system (henceforth, "security AI/ML" or "security AI/ML system ...
Machine Learning Ieee Papers and Projects-2020
MACHINE LEARNING IEEE PAPERS AND PROJECTS-2020. Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for ...
Machine Learning Aspects and its Applications Towards ...
Machine learning is a branch of artificial intelligence that aims at enabling machines to perform their jobs skillfully by using intelligent software. The statistical learning methods constitute the backbone of intelligent software that is used to develop machine intelligence. Now a Day, a huge increase in demand for machine learning has been seen with the great number of available datasets ...
2024 Conference
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.
2023 IEEE International Conference on Machine Learning and Applied
Read all the papers in 2023 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) | IEEE Conference | IEEE Xplore
COMMENTS
Machine Learning. Abstract: 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.
Nowadays, large amount of data is available everywhere. Therefore, it is very important to analyze this data in order to extract some useful information and to develop an algorithm based on this analysis. This can be achieved through data mining and machine learning. Machine learning is an integral part of artificial intelligence, which is used to design algorithms based on the data trends and ...
This paper aims to use various machine learning algorithms and explore the influence between different algorithms and multi-feature in the time series. The real consumption records constitute the time series as the research object. We extract consumption mark, frequency and other features. Moreover, we utilize support vector machine (SVM), long short-term memory (LSTM) and other algorithms to ...
Abstract— In this paper, a novel system architecture including a massive multi-input multi-output (MIMO) or a reconfigurable intelligent surface (RIS) and multiple autonomous vehicles is considered in vehicle location systems. Autonomous Vehicles Super-Resolution. Paper. Add Code.
This review provides a broad and detailed overview of studies for code generation using ML. We selected 37 publications indexed in arXiv and IEEE Xplore databases that train ML models on programming language data to generate code. The three paradigms of code generation we identified in these studies are description-to-code, code-to-description ...
Computational Media Intelligence: Human-Centered Machine Analysis of Media. By K. Somandepalli, T. Guha, V. R. Martinez, N. Kumar, H. Adam, and S. Narayanan. The topic treated in this article is the application of deep learning algorithms, combined with audio-visual signal processing, to analyze entertainment media such as film/TV.
In this paper, an intelligent identification method for rail vehicle running state is proposed based on Tiny Machine Learning (TinyML) technology, and an IoT system is developed with small size and low energy consumption. The system uses a Micro-Electro-Mechanical System (MEMS) sensor to collect acceleration data for machine learning training.
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.
research in the field. Index Terms—deep learning, neural networks, natural lan-guage processing, computational linguistics, machine learning I. INTRODUCTION T HE field of natural language processing (NLP) encom-passes a variety of topics which involve the compu-tational processing and understanding of human languages.
s social systems, ecosystems, biological networks, knowledge graphs, and information systems. With the continuous penetra-tion of artificial intelligence technologies, graph learning (i. e., machine learning on graphs) is gaining attention from both researchers and practitioners. Graph le. rning proves effective for many tasks, such as ...
Machine learning is a relatively new field. With the deepening of people's research in this field, the application of machine learning is increasingly extensive. On the other hand, with the advancement of science and technology, graphics have been an indispensable medium of information transmission, and image processing technology is also booming. However, the traditional image processing ...
IEEE TMLCN also particularly encourages the submission of papers that simultaneously advance both the fields of machine learning and wireless networking. The journal also advocates for reproducible and public sharing of codes, datasets, software, and other artefacts related to research contributions.
Comparison of Classification Techniques used in **Machine Learning** as Applied on Vocational Guidance Data. Traffic Prediction for Intelligent Transportation System using **Machine Learning**. Audio, Speech, and Language Processing, IEEE Transactions on. Automatic Control, IEEE Transactions on.
Efficient Acceleration of Deep Learning Inference on Resource-Constrained Edge Devices: A Review. By M. M. Hossain Shuvo, S. K. Islam, J. Cheng, and B. I. Morshed. This article provides a comprehensive review of the state-of-the-art tools and techniques for efficient edge inference, a vital element of artificial intelligence on edge.
Most modern machine learning research is devoted to improving the accuracy of prediction. However, less attention is paid to the deployment of the machine and deep learning systems, supervised ...
discusses some possible open areas of research and future directions, whereas Section VIII concludes the paper. II. OVERVIEW OF MACHINE LEARNING METHODS USED IN OPTICAL NETWORKS This section provides an overview of some of the most popular algorithms that are commonly classified as machine learning. The literature on ML is so extensive that even a
Two new analyses put the spotlight on machine learning in health research, where lack of reproducibility and poor quality is especially alarming. "If a doctor is using machine learning or an ...
Abstract: In the evolution of artificial Intelligence (AI) and machine learning (ML), reasoning, knowledge representation, planning, learning, natural language processing, perception, and the ability to move and manipulate objects have been widely used. These features enable the creation of intelligent mechanisms for decision support to overcome the limits of human knowledge processing.
Moroccan Dialect Emotion Recognition Dataset. Moroccan Dialect Emotion Recognition Dataset is a collection of voice records of people speaking Moroccan dialect in 5 states of emotion: Neutral, Happy, Sad, Angry and Fearful. The dataset has been collected in different Moroccan cities in 2024. Each recorder has 5 records per emotion class.
The opportunity, nearly a necessity, is for security artificial intelligence (AI)/machine learning (ML) to act as a force multiplier by augmenting the cybersecurity workforce's ability to defend at scale and speed. The agility created by AI/ML augmentation of a cybersecurity system (henceforth, "security AI/ML" or "security AI/ML system ...
MACHINE LEARNING IEEE PAPERS AND PROJECTS-2020. Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for ...
Machine learning is a branch of artificial intelligence that aims at enabling machines to perform their jobs skillfully by using intelligent software. The statistical learning methods constitute the backbone of intelligent software that is used to develop machine intelligence. Now a Day, a huge increase in demand for machine learning has been seen with the great number of available datasets ...
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.
Read all the papers in 2023 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) | IEEE Conference | IEEE Xplore