Results 21 to 30 of about 8,744,617 (299)
LoRaWAN Meets ML: A Survey on Enhancing Performance with Machine Learning
Sensors, 2023 The Internet of Things is rapidly growing with the demand for low-power, long-range wireless communication technologies. Long Range Wide Area Network (LoRaWAN) is one such technology that has gained significant attention in recent years due to its ...
Arshad Farhad, Jae-Young Pyun
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Automated Machine Learning [PDF]
, 2019 This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of ...
core +1 more source
Multilayer Fisher extreme learning machine for classification
Complex & Intelligent Systems, 2022 As a special deep learning algorithm, the multilayer extreme learning machine (ML-ELM) has been extensively studied to solve practical problems in recent years.
Jie Lai +4 more
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Vertica-ML: Distributed Machine Learning in Vertica Database [PDF]
Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, 2020 A growing number of companies rely on machine learning as a key element for gaining a competitive edge from their collected Big Data. An in-database machine learning system can provide many advantages in this scenario, e.g., eliminating the overhead of data transfer, avoiding the maintenance costs of a separate analytical system, and addressing data ...
Arash Fard +4 more
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Machine learning methods for optical communications
, 2020 Radio over Fiber (RoF) technology has been realized in different forms ranging from analog to more complex forms [1-6]. The enhancement of capacity and wireless coverage has posed significant challenges to the existing optical and wireless access ...
Machine learning methods for optical communications
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Galaxy-ML: An accessible, reproducible, and scalable machine learning toolkit for biomedicine.
PLoS Computational Biology, 2021 Supervised machine learning is an essential but difficult to use approach in biomedical data analysis. The Galaxy-ML toolkit (https://galaxyproject.org/community/machine-learning/) makes supervised machine learning more accessible to biomedical ...
Qiang Gu +7 more
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ml-Codesmell: A code smell prediction dataset for machine learning approaches.
, 2022 The ml-Codesmell dataset was created by analyzing source code and extracting massive source code metrics with many labelled code smells. This dataset has been used to train and predict code smell using machine learning algorithms.
Binh Nguyen Thanh (13965230) +3 more
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Seagrass classification using unsupervised curriculum learning (UCL)
Ecological InformaticsSeagrass ecosystems are pivotal in marine environments, serving as crucial habitats for diverse marine species and contributing significantly to carbon sequestration.
Nosheen Abid +7 more
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Interactive Automation Of COVID-19 Classification Through X-Ray Images Using Machine Learning
JISR on Computing, 2020 Machine learning had given many benefits to the humankind by implementing technology on the daily human lives. To add, when the pandemic COVID19 hits Earth globally in early 2020, mankind is challenged with the sudden emergence of the virus that costed
Ashura binti Hasmadi +2 more
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Snap ML: A Hierarchical Framework for Machine Learning
CoRR, 2018 We describe a new software framework for fast training of generalized linear models. The framework, named Snap Machine Learning (Snap ML), combines recent advances in machine learning systems and algorithms in a nested manner to reflect the hierarchical architecture of modern computing systems. We prove theoretically that such a hierarchical system can
Celestine Dünner +7 more
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