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Refinado por: assunto: Computer Science, Artificial Intelligence remover
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Subjective Logic: A Formalism for Reasoning under Uncertainty
Subjective Logic: A Formalism for Reasoning under Uncertainty
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Subjective Logic: A Formalism for Reasoning under Uncertainty

Jøsang, Audun

Cham: Springer International Publishing AG 2016

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12
On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)
On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)
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On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)

Washim Uddin Mondal ; Agarwal, Mridul ; Aggarwal, Vaneet ; Ukkusuri, Satish V

arXiv.org, 2022-01 [Periódico revisado por pares]

Ithaca: Cornell University Library, arXiv.org

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13
Subject-Independent Brain-Computer Interfaces Based on Deep Convolutional Neural Networks
Subject-Independent Brain-Computer Interfaces Based on Deep Convolutional Neural Networks
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Subject-Independent Brain-Computer Interfaces Based on Deep Convolutional Neural Networks

Kwon, O-Yeon ; Lee, Min-Ho ; Guan, Cuntai ; Lee, Seong-Whan

IEEE transaction on neural networks and learning systems, 2020-10, Vol.31 (10), p.3839-3852

United States: IEEE

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14
Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks
Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks
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Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks

Fan, Deng-Ping ; Lin, Zheng ; Zhang, Zhao ; Zhu, Menglong ; Cheng, Ming-Ming

IEEE transaction on neural networks and learning systems, 2021-05, Vol.32 (5), p.2075-2089

United States: IEEE

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15
Internal Feature Selection Method of CSP Based on L1-Norm and Dempster-Shafer Theory
Internal Feature Selection Method of CSP Based on L1-Norm and Dempster-Shafer Theory
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Internal Feature Selection Method of CSP Based on L1-Norm and Dempster-Shafer Theory

Jin, Jing ; Xiao, Ruocheng ; Daly, Ian ; Miao, Yangyang ; Wang, Xingyu ; Cichocki, Andrzej

IEEE transaction on neural networks and learning systems, 2021-11, Vol.32 (11), p.4814-4825

United States: IEEE

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16
Privacy and Robustness in Federated Learning: Attacks and Defenses
Privacy and Robustness in Federated Learning: Attacks and Defenses
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Privacy and Robustness in Federated Learning: Attacks and Defenses

Lyu, Lingjuan ; Yu, Han ; Ma, Xingjun ; Chen, Chen ; Sun, Lichao ; Zhao, Jun ; Yang, Qiang ; Yu, Philip S.

IEEE transaction on neural networks and learning systems, 2024-07, Vol.35 (7), p.8726-8746

United States: IEEE

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17
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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18
A content-based recommender system for computer science publications
A content-based recommender system for computer science publications
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A content-based recommender system for computer science publications

Wang, Donghui ; Liang, Yanchun ; Xu, Dong ; Feng, Xiaoyue ; Guan, Renchu

Knowledge-based systems, 2018-10, Vol.157, p.1-9 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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19
A Survey on Knowledge Graphs: Representation, Acquisition, and Applications
A Survey on Knowledge Graphs: Representation, Acquisition, and Applications
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A Survey on Knowledge Graphs: Representation, Acquisition, and Applications

Ji, Shaoxiong ; Pan, Shirui ; Cambria, Erik ; Marttinen, Pekka ; Yu, Philip S.

IEEE transaction on neural networks and learning systems, 2022-02, Vol.33 (2), p.494-514

United States: IEEE

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20
Adversarial Examples: Attacks and Defenses for Deep Learning
Adversarial Examples: Attacks and Defenses for Deep Learning
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Adversarial Examples: Attacks and Defenses for Deep Learning

Yuan, Xiaoyong ; He, Pan ; Zhu, Qile ; Li, Xiaolin

IEEE transaction on neural networks and learning systems, 2019-09, Vol.30 (9), p.2805-2824

United States: IEEE

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