Zehui Xiong
Artificial Intelligence · 2017–2023
A researcher in the Science corpus: 18 papers; trusts 118 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 285 citations into it; #26,233 of 35,345 by trust here, #9,092 by citations
- Computer Networks and Communications — 166 citations into it
- Electrical and Electronic Engineering — 138 citations into it
- Computer Vision and Pattern Recognition — 136 citations into it
- Information Systems — 121 citations into it; #5,891 of 8,771 by trust here, #1,362 by citations
- Federated & Distributed Learning — 42 citations into it
- Aerospace Engineering — 39 citations into it
- Efficiency & Compression — 27 citations into it
Whom Zehui Xiong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jiawen Kang
- Geoffrey E. Hinton
- Jakub Konecný
- Alex Krizhevsky
- Clement Fung
- Kaiming He
- Yoshua Bengio
- Dusist Niyato
- Yann LeCun
- Diederik P. Kingma
Who trusts Zehui Xiong overall
- Jiawen Kang
- Dinh C. Nguyen
- Dusist Niyato
- Keke Gai
- Yuanming Shi
- Hongning Dai
- Wenbo Wang
- Amal Feriani
- Yi Liu
- Minrui Xu
Papers from Zehui Xiong's perspective
Ordered by how strongly the researchers Zehui Xiong trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Deep Reinforcement Learning-Based Intelligent Reflecting Surface for Secure Wireless Communications (2020) — 410 citations
- Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning (2020) — 26 citations
- Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach (2019) — 249 citations
- Artificial-Intelligence-Enabled Intelligent 6G Networks (2019) — 438 citations
- Federated learning for 6G communications: Challenges, methods, and future directions (2020) — 331 citations
- Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach (2020) — 273 citations
- Covert Communications: A Comprehensive Survey (2023) — 364 citations
- Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Services (2023) — 381 citations
- A Full Dive Into Realizing the Edge-Enabled Metaverse: Visions, Enabling Technologies, and Challenges (2022) — 468 citations
- Fusing Blockchain and AI With Metaverse: A Survey (2022) — 374 citations
- Semantic Communications for Future Internet: Fundamentals, Applications, and Challenges (2022) — 646 citations
- Deep Anomaly Detection for Time-Series Data in Industrial IoT: A Communication-Efficient On-Device Federated Learning Approach (2020) — 497 citations
- Reliable Federated Learning for Mobile Networks (2019) — 561 citations
- Incentivizing Consensus Propagation in Proof-of-Stake Based Consortium Blockchain Networks (2019) — 88 citations
- Incentive Mechanism for Reliable Federated Learning: A Joint Optimization Approach to Combining Reputation and Contract Theory (2019) — 793 citations
- A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks (2018) — 840 citations
- Toward Secure Blockchain-Enabled Internet of Vehicles: Optimizing Consensus Management Using Reputation and Contract Theory (2018) — 523 citations
- When Mobile Blockchain Meets Edge Computing (2017) — 481 citations