Kin Kwong Leung
Computer Networks and Communications · 2007–2018
A researcher in the Science corpus: 9 papers; trusts 40 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 102 citations into it; #2,983 of 9,886 by trust here, #322 by citations
- Electrical and Electronic Engineering — 78 citations into it
- Artificial Intelligence — 43 citations into it; #22,572 of 35,345 by trust here, #7,471 by citations
- Optimization & Training — 26 citations into it
- Ocean Engineering — 23 citations into it
- Computer Vision and Pattern Recognition — 21 citations into it
- Computational Mechanics — 13 citations into it
- Management Science and Operations Research — 11 citations into it
Whom Kin Kwong Leung trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- L. Eon Bottou
- Andrea J. Goldsmith
- Shai Shalev-Shwartz
- Yann LeCun
- Alex Krizhevsky
- Ossama Younis
- Xu Ning
- Wei Ye
- Wendi Rabiner Heinzelman
- Jie Xiong
Who trusts Kin Kwong Leung overall
Papers from Kin Kwong Leung's perspective
Ordered by how strongly the researchers Kin Kwong Leung trusts endorse each paper. Same corpus, a different order for every researcher.
- Gradient-based learning applied to document recognition
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Reinforcement Learning: An Introduction
Their papers
- Adaptive Federated Learning in Resource Constrained Edge Computing Systems (2018) — 2,085 citations
- MAC Essentials for Wireless Sensor Networks (2010) — 613 citations
- A Survey of Indoor Localization Systems and Technologies (2017) — 2,233 citations
- When Edge Meets Learning: Adaptive Control for Resource-Constrained Distributed Machine Learning (2018) — 487 citations
- Demo abstract: Distributed machine learning at resource-limited edge nodes (2018) — 31 citations
- Distributed Machine Learning in Coalition Environments: Overview of Techniques (2018) — 15 citations
- Dynamic Service Placement for Mobile Micro-Clouds with Predicted Future Costs (2015) — 258 citations
- A survey on the ietf protocol suite for the internet of things: standards, challenges, and opportunities (2013) — 790 citations
- A dynamic clustering and energy efficient routing technique for sensor networks (2007) — 149 citations