Results 31 to 40 of about 2,506,404 (226)
Industry-scale application and evaluation of deep learning for drug target prediction [PDF]
, 2019 Artificial intelligence (AI) is undergoing a revolution thanks to the breakthroughs of machine learning algorithms in computer vision, speech recognition, natural language processing and generative modelling.
Ashby, Thomas J. +18 more
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Journal of Physics A: Mathematical and Theoretical, 2020 Abstract Machine learning methods have had spectacular success on numerous problems. Here we show that a prominent class of learning algorithms—including support vector machines (SVMs)—have a natural interpretation in terms of ecological dynamics. We use these ideas to design new online SVM algorithms that exploit ecological invasions,
Owen Howell +3 more
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Supervised Learning in Physical Networks: From Machine Learning to Learning Machines [PDF]
Physical Review X, 2021 18 pages, 9 ...
Menachem Stern +3 more
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Distributional Prototypical Methods for Reliable Explanation Space Construction
IEEE Access, 2023 As deep learning has been successfully deployed in diverse applications, there is an ever increasing need to explain its decision. To explain decisions, case-based reasoning has proved to be effective in many areas.
Hyungjun Joo +3 more
doaj +1 more source
Quantum-chemical insights from deep tensor neural networks
Nature Communications, 2017 Machine learning is an increasingly popular approach to analyse data and make predictions. Here the authors develop a ‘deep learning’ framework for quantitative predictions and qualitative understanding of quantum-mechanical observables of chemical ...
Kristof T. Schütt +4 more
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Power Allocation Schemes Based on Deep Learning for Distributed Antenna Systems
IEEE Access, 2020 In recent years, a lot of power allocation algorithms have been proposed to maximize spectral efficiency (SE) and energy efficiency (EE) for the distributed antenna systems (DAS).
Gongbin Qian +4 more
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Introduction to Machine Learning [PDF]
, 2013 The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely
Baştanlar, Yalın, Özuysal, Mustafa
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A Shared Task on Bandit Learning for Machine Translation
, 2017 We introduce and describe the results of a novel shared task on bandit learning for machine translation. The task was organized jointly by Amazon and Heidelberg University for the first time at the Second Conference on Machine Translation (WMT 2017). The
Danchenko, Pavel +6 more
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The Machine Learning Machine: A Tangible User Interface for Teaching Machine Learning
Proceedings of the Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction, 2021 Machine Learning (ML) is often used invisibly in everyday applications with little opportunity for consumers to investigate how it works. In this paper, we expand recent efforts to unfold what students should know about ML and how to design tools and activities allowing them to engage with ML.
Magnus Høholt Kaspersen +2 more
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The scientific evaluation of music content analysis systems: Valid empirical foundations for future real-world impact [PDF]
, 2016 We discuss the problem of music content analysis within the formal framework of experimental ...
Grossmann, H +4 more
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