Kezhi Mao
Control and Systems Engineering · 2004–2019
A researcher in the Science corpus: 4 papers; trusts 16 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Control and Systems Engineering — 46 citations into it; #1,653 of 8,257 by trust here, #1,631 by citations
- Artificial Intelligence — 32 citations into it; #30,127 of 35,345 by trust here, #10,319 by citations
- Computer Vision and Pattern Recognition — 18 citations into it
- Model Architectures — 16 citations into it
- Representation & Self-Supervised Learning — 12 citations into it
- Natural Language Processing — 7 citations into it
- Signal Processing — 7 citations into it
Whom Kezhi Mao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ron Kohavi
- Anil K. Jain
- Josef Kittler
- George H. John
- Geoffrey E. Hinton
- Karthik Nandakumar
- Yoshua Bengio
- Arun A. Ross
- J. Urgen Schmidhuber
- Sepp Hochreiter
Who trusts Kezhi Mao overall
Papers from Kezhi Mao's perspective
Ordered by how strongly the researchers Kezhi Mao 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)
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
Their papers
- Deep learning and its applications to machine health monitoring (2019) — 2,506 citations
- Machine Health Monitoring Using Local Feature-Based Gated Recurrent Unit Networks (2018) — 735 citations
- Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks (2017) — 691 citations
- Orthogonal forward selection and backward elimination algorithms for feature subset selection (2004) — 231 citations