Kenneth T. Co

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 275 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 71 citations into it; #21,232 of 35,345 by trust here, #24,417 by citations
• Safety, Robustness & Interpretability — 48 citations into it
• Computer Vision and Pattern Recognition — 38 citations into it
• Signal Processing — 20 citations into it
• Computer Networks and Communications — 12 citations into it
• Optimization & Training — 8 citations into it
• Federated & Distributed Learning — 7 citations into it
• Model Architectures — 6 citations into it

Whom Kenneth T. Co trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alex Krizhevsky
2. Ian J. Goodfellow
3. Ross B. Girshick
4. Geoffrey E. Hinton
5. Christian Szegedy
6. Kaiming He
7. Karen Simonyan
8. Yann LeCun
9. Yoshua Bengio
10. Nicholas Carlini

Who trusts Kenneth T. Co overall

1. Li Li
2. Lie He
3. Eugene Bagdasarian

Papers from Kenneth T. Co's perspective

Ordered by how strongly the researchers Kenneth T. Co trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks (2018) — 78 citations
• Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging (2019) — 229 citations