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A Survey of the Usages of Deep Learning for Natural Language Processing
A Survey of the Usages of Deep Learning for Natural Language Processing
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A Survey of the Usages of Deep Learning for Natural Language Processing

Otter, Daniel W. ; Medina, Julian R. ; Kalita, Jugal K.

IEEE transaction on neural networks and learning systems, 2021-02, Vol.32 (2), p.604-624

United States: IEEE

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Notions of architecture in fog computing
Notions of architecture in fog computing
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Notions of architecture in fog computing

Mann, Zoltán Ádám

Computing, 2021, Vol.103 (1), p.51-73 [Periódico revisado por pares]

Vienna: Springer Vienna

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3
On the Complexity of Neural Network Classifiers: A Comparison Between Shallow and Deep Architectures
On the Complexity of Neural Network Classifiers: A Comparison Between Shallow and Deep Architectures
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On the Complexity of Neural Network Classifiers: A Comparison Between Shallow and Deep Architectures

Bianchini, Monica ; Scarselli, Franco

IEEE transaction on neural networks and learning systems, 2014-08, Vol.25 (8), p.1553-1565

New York, NY: IEEE

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4
Efficient Online Learning Algorithms Based on LSTM Neural Networks
Efficient Online Learning Algorithms Based on LSTM Neural Networks
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Efficient Online Learning Algorithms Based on LSTM Neural Networks

Ergen, Tolga ; Kozat, Suleyman Serdar

IEEE transaction on neural networks and learning systems, 2018-08, Vol.29 (8), p.3772-3783

United States: IEEE

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5
Applications of Deep Learning and Reinforcement Learning to Biological Data
Applications of Deep Learning and Reinforcement Learning to Biological Data
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Applications of Deep Learning and Reinforcement Learning to Biological Data

Mahmud, Mufti ; Kaiser, Mohammed Shamim ; Hussain, Amir ; Vassanelli, Stefano

IEEE transaction on neural networks and learning systems, 2018-06, Vol.29 (6), p.2063-2079

United States: IEEE

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6
The individual identification method of wireless device based on dimensionality reduction and machine learning
The individual identification method of wireless device based on dimensionality reduction and machine learning
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The individual identification method of wireless device based on dimensionality reduction and machine learning

Lin, Yun ; Zhu, Xiaolei ; Zheng, Zhigao ; Dou, Zheng ; Zhou, Ruolin

The Journal of supercomputing, 2019-06, Vol.75 (6), p.3010-3027 [Periódico revisado por pares]

New York: Springer US

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7
Learning Temporal Information for Brain-Computer Interface Using Convolutional Neural Networks
Learning Temporal Information for Brain-Computer Interface Using Convolutional Neural Networks
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Learning Temporal Information for Brain-Computer Interface Using Convolutional Neural Networks

Sakhavi, Siavash ; Guan, Cuntai ; Yan, Shuicheng

IEEE transaction on neural networks and learning systems, 2018-11, Vol.29 (11), p.5619-5629

United States: IEEE

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8
A Proof of the CSP Dichotomy Conjecture
A Proof of the CSP Dichotomy Conjecture
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A Proof of the CSP Dichotomy Conjecture

Zhuk, Dmitriy

Journal of the ACM, 2020-10, Vol.67 (5), p.1-78 [Periódico revisado por pares]

New York: Association for Computing Machinery

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9
Fully Functional Suffix Trees and Optimal Text Searching in BWT-Runs Bounded Space
Fully Functional Suffix Trees and Optimal Text Searching in BWT-Runs Bounded Space
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Fully Functional Suffix Trees and Optimal Text Searching in BWT-Runs Bounded Space

Gagie, Travis ; Navarro, Gonzalo ; Prezza, Nicola

Journal of the ACM, 2020-01, Vol.67 (1), p.1-54 [Periódico revisado por pares]

New York: Association for Computing Machinery

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10
fpgaConvNet: Mapping Regular and Irregular Convolutional Neural Networks on FPGAs
fpgaConvNet: Mapping Regular and Irregular Convolutional Neural Networks on FPGAs
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fpgaConvNet: Mapping Regular and Irregular Convolutional Neural Networks on FPGAs

Venieris, Stylianos I. ; Bouganis, Christos-Savvas

IEEE transaction on neural networks and learning systems, 2019-02, Vol.30 (2), p.326-342

United States: IEEE

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