Jiawen Kang
Artificial Intelligence · IEEE Transactions on Industrial Informatics · 2017–2023
A researcher in the Science corpus: 15 papers; trusts 42 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 199 citations into it; #19,103 of 35,345 by trust here, #7,062 by citations
- Computer Networks and Communications — 109 citations into it
- Computer Vision and Pattern Recognition — 95 citations into it
- Electrical and Electronic Engineering — 78 citations into it; #6,516 of 16,539 by trust here, #3,580 by citations
- Information Systems — 66 citations into it; #2,692 of 8,771 by trust here, #541 by citations
- Federated & Distributed Learning — 44 citations into it
- Computer Science Applications — 27 citations into it
- Efficiency & Compression — 25 citations into it
Whom Jiawen Kang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Clement Fung
- Zehui Xiong
- Zhanwei Hou
- Dusist Niyato
- Jakub Konecný
- Yong Yuan
- Muhammad Shayan
- Rong Yu
- Yan Zhang
- Anthony Dewayne Hunt
Who trusts Jiawen Kang overall
- Zehui Xiong
- Dusist Niyato
- Wayes Tushar
- Dinh C. Nguyen
- Keke Gai
- Yue Zhou
- Dongdong Ye
- Yi Liu
- Sabita Maharjan
- Priyanka Mary Mammen
Papers from Jiawen Kang's perspective
Ordered by how strongly the researchers Jiawen Kang 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
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Distilling the Knowledge in a Neural Network (arXiv.org)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach (2019) — 249 citations
- Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks (2019) — 653 citations
- Enabling Localized Peer-to-Peer Electricity Trading Among Plug-in Hybrid Electric Vehicles Using Consortium Blockchains (2017) — 1,001 citations
- Federated learning for 6G communications: Challenges, methods, and future directions (2020) — 331 citations
- Privacy-Preserving Traffic Flow Prediction: A Federated Learning Approach (2020) — 549 citations
- Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach (2020) — 273 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
- 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
- Consortium Blockchain for Secure Energy Trading in Industrial Internet of Things (2018) — 963 citations
- Toward Secure Blockchain-Enabled Internet of Vehicles: Optimizing Consensus Management Using Reputation and Contract Theory (2018) — 523 citations