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Refinado por: assunto: Computer Science, Theory & Methods remover assunto: Algorithms remover
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Scene Recognition by Manifold Regularized Deep Learning Architecture
Scene Recognition by Manifold Regularized Deep Learning Architecture
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Scene Recognition by Manifold Regularized Deep Learning Architecture

Yuan, Yuan ; Mou, Lichao ; Lu, Xiaoqiang

IEEE transaction on neural networks and learning systems, 2015-10, Vol.26 (10), p.2222-2233

United States: IEEE

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An Approach for Service Function Chain Routing and Virtual Function Network Instance Migration in Network Function Virtualization Architectures
An Approach for Service Function Chain Routing and Virtual Function Network Instance Migration in Network Function Virtualization Architectures
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An Approach for Service Function Chain Routing and Virtual Function Network Instance Migration in Network Function Virtualization Architectures

Eramo, Vincenzo ; Miucci, Emanuele ; Ammar, Mostafa ; Lavacca, Francesco Giacinto

IEEE/ACM transactions on networking, 2017-08, Vol.25 (4), p.2008-2025 [Periódico revisado por pares]

New York: IEEE

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3
Automatic Searching and Pruning of Deep Neural Networks for Medical Imaging Diagnostic
Automatic Searching and Pruning of Deep Neural Networks for Medical Imaging Diagnostic
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Automatic Searching and Pruning of Deep Neural Networks for Medical Imaging Diagnostic

Fernandes, Francisco Erivaldo ; Yen, Gary G.

IEEE transaction on neural networks and learning systems, 2021-12, Vol.32 (12), p.5664-5674

United States: IEEE

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4
A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions
A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions
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A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions

Ren, Pengzhen ; Xiao, Yun ; Chang, Xiaojun ; Huang, Po-yao ; Li, Zhihui ; Chen, Xiaojiang ; Wang, Xin

ACM computing surveys, 2021-07, Vol.54 (4), p.1-34 [Periódico revisado por pares]

Baltimore: Association for Computing Machinery

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5
An innovative neural network approach for stock market prediction
An innovative neural network approach for stock market prediction
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An innovative neural network approach for stock market prediction

Pang, Xiongwen ; Zhou, Yanqiang ; Wang, Pan ; Lin, Weiwei ; Chang, Victor

The Journal of supercomputing, 2020-03, Vol.76 (3), p.2098-2118 [Periódico revisado por pares]

New York: Springer US

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6
A Survey of IoT Applications in Blockchain Systems: Architecture, Consensus, and Traffic Modeling
A Survey of IoT Applications in Blockchain Systems: Architecture, Consensus, and Traffic Modeling
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A Survey of IoT Applications in Blockchain Systems: Architecture, Consensus, and Traffic Modeling

Lao, Laphou ; Li, Zecheng ; Hou, Songlin ; Xiao, Bin ; Guo, Songtao ; Yang, Yuanyuan

ACM computing surveys, 2020-02, Vol.53 (1), p.1-32 [Periódico revisado por pares]

Baltimore: ACM

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7
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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8
Supporting runtime software architecture: A bidirectional-transformation-based approach
Supporting runtime software architecture: A bidirectional-transformation-based approach
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Supporting runtime software architecture: A bidirectional-transformation-based approach

Song, Hui ; Huang, Gang ; Chauvel, Franck ; Xiong, Yingfei ; Hu, Zhenjiang ; Sun, Yanchun ; Mei, Hong

The Journal of systems and software, 2011-05, Vol.84 (5), p.711-723 [Periódico revisado por pares]

New York: Elsevier Inc

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9
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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10
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: ACM

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