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International Journal of Semantic Computing, 2016
Deep learning is a branch of machine learning that tries to model high-level abstractions of data using multiple layers of neurons consisting of complex structures or non-liner transformations. With the increase of the amount of data and the power of computation, neural networks with more complex structures have attracted widespread attention and been
Xing Hao, Guigang Zhang, Shang Ma
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Deep learning is a branch of machine learning that tries to model high-level abstractions of data using multiple layers of neurons consisting of complex structures or non-liner transformations. With the increase of the amount of data and the power of computation, neural networks with more complex structures have attracted widespread attention and been
Xing Hao, Guigang Zhang, Shang Ma
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Encyclopedia with Semantic Computing and Robotic Intelligence, 2017
Artificial intelligence is one of the most beautiful dreams of mankind. Although computer technology has made considerable progress, so far, there is no computer showing intelligence like human beings. The emergence of deep learning gives people a glimmer of hope. So, what is learning deep? Why is it so important? How does it work?
Xing Hao, Guigang Zhang
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Artificial intelligence is one of the most beautiful dreams of mankind. Although computer technology has made considerable progress, so far, there is no computer showing intelligence like human beings. The emergence of deep learning gives people a glimmer of hope. So, what is learning deep? Why is it so important? How does it work?
Xing Hao, Guigang Zhang
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2019
The chapter is devoted at illustrating the basic principles and the current results which characterize the research on Deep Learning. The term refers to the theory and practice of devising and training complex neural networks for supervised and unsupervised tasks.
Massimo Guarascio +2 more
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The chapter is devoted at illustrating the basic principles and the current results which characterize the research on Deep Learning. The term refers to the theory and practice of devising and training complex neural networks for supervised and unsupervised tasks.
Massimo Guarascio +2 more
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Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, 2014
Building intelligent systems that are capable of extracting high-level representations from high-dimensional data lies at the core of solving many AI related tasks, including visual object or pattern recognition, speech perception, and language understanding. Theoretical and biological arguments strongly suggest that building such systems requires deep
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Building intelligent systems that are capable of extracting high-level representations from high-dimensional data lies at the core of solving many AI related tasks, including visual object or pattern recognition, speech perception, and language understanding. Theoretical and biological arguments strongly suggest that building such systems requires deep
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Nature Computational Science, 2021
The computational complexity of deep neural networks is a major obstacle of many application scenarios driven by low-power devices, including federated learning. A recent finding shows that random sketches can substantially reduce the model complexity without affecting prediction accuracy.
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The computational complexity of deep neural networks is a major obstacle of many application scenarios driven by low-power devices, including federated learning. A recent finding shows that random sketches can substantially reduce the model complexity without affecting prediction accuracy.
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Proceedings of the 24th International Conference on World Wide Web, 2015
Deep learning is a machine learning technology that automatically extracts higher-level representations from raw data by stacking multiple layers of neuron-like units. The stacking allows for extracting representations of increasingly-complex features without time-consuming, offline feature engineering. Recent success of deep learning has shown that it
Kyomin Jung +2 more
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Deep learning is a machine learning technology that automatically extracts higher-level representations from raw data by stacking multiple layers of neuron-like units. The stacking allows for extracting representations of increasingly-complex features without time-consuming, offline feature engineering. Recent success of deep learning has shown that it
Kyomin Jung +2 more
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On Definition of Deep Learning
2018 World Automation Congress (WAC), 2018Deep learning has become a buzz word recently. However, there is a lack of unified definition to deep learning in literature. The goal of this paper is to overview various definitions to deep learning and to show their limitations. Finally, a unified or more general definition to deep learning is given. The paper also outlines a general methodology for
Wen-Jun Zhang 0005 +4 more
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2020
We introduce an overview of methods for learning in structured domains covering foundational works developed within the last twenty years to deal with a whole range of complex data representations, including hierarchical structures, graphs and networks, and giving special attention to recent deep learning models for graphs.
Bacciu D., Micheli A.
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We introduce an overview of methods for learning in structured domains covering foundational works developed within the last twenty years to deal with a whole range of complex data representations, including hierarchical structures, graphs and networks, and giving special attention to recent deep learning models for graphs.
Bacciu D., Micheli A.
openaire +3 more sources