Tao Li

Artificial Intelligence · with Adjeroh · 2017–2020

A researcher in the Science corpus: 2 papers; trusts 28 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 28 citations into it; #30,824 of 35,345 by trust here, #25,040 by citations
• Signal Processing — 28 citations into it; #6,666 of 7,572 by trust here, #5,570 by citations
• Computer Networks and Communications — 23 citations into it; #8,476 of 9,886 by trust here, #6,217 by citations
• Information Systems — 18 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it
• Software — 7 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Tao Li trusts overall

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

1. Yoshua Bengio
2. Leo Breiman
3. Ulrich Bayer
4. Thomas G. Dietterich
5. William W. Cohen
6. Yoav Freund
7. Fabrizio Sebastiani
8. Alain Rakotomamonjy
9. Lior Rokach
10. Heng Yin

Who trusts Tao Li overall

1. Raghavendra Chalapathy
2. Ori Or-Meir

Papers from Tao Li's perspective

Ordered by how strongly the researchers Tao Li 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• DeepFed: Federated Deep Learning for Intrusion Detection in Industrial Cyber–Physical Systems (2020) — 455 citations
• A Survey on Malware Detection Using Data Mining Techniques (2017) — 612 citations