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The publications of the Institute of Electrical and Electronics Engineers (IEEE) constitute around 30% of the world literature in the electrical and electronics engineering and computer science fields, [citation needed] publishing well over 100 peer-reviewed journals. [1]
IEEE Transactions on Neural Networks and Learning Systems is a monthly peer-reviewed scientific journal published by the IEEE Computational Intelligence Society. It covers the theory, design, and applications of neural networks and related learning systems. According to the Journal Citation Reports, the journal had a 2021 impact factor of 14. ...
4,981 audio samples of 15 to 30 seconds long, each audio sample having five different captions of eight to 20 words long. 24,905 Sound and text Automated audio captioning 2020 [152] [153] K. Drossos, S. Lipping, and T. Virtanen
This model paved the way for research to split into two approaches. One approach focused on biological processes while the other focused on the application of neural networks to artificial intelligence. In the late 1940s, D. O. Hebb [14] proposed a learning hypothesis based on the mechanism of neural plasticity that became known as Hebbian ...
Along with ICLR and ICML, it is one of the three primary conferences of high impact in machine learning and artificial intelligence research. [ 1 ] The conference is currently a double-track meeting (single-track until 2015) that includes invited talks as well as oral and poster presentations of refereed papers, followed by parallel-track ...
The IEEE Transactions on Learning Technologies (TLT) is a peer-reviewed scientific journal covering advances in the development of technologies for supporting human learning. It was established in 2008 and is published by the IEEE Education Society. [1] The current editor-in-chief (since 2022) is Minjuan Wang of San Diego State University.
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]
Machine learning (ML) is a subfield of artificial intelligence within computer science that evolved from the study of pattern recognition and computational learning theory. [1] In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". [ 2 ]