Lei Yu

Artificial Intelligence · IEEE Transactions on Knowledge and Data Engineering · 2003–2005

A researcher in the Science corpus: 4 papers; trusts 25 researchers and is trusted by 80 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it; #3,252 of 35,345 by trust here, #7,858 by citations
• Information Systems — 13 citations into it; #292 of 8,771 by trust here, #1,086 by citations
• Statistical Learning Theory — 13 citations into it
• Evaluation & Benchmarks — 9 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it; #3,514 of 21,575 by trust here, #6,089 by citations
• Molecular Biology — 6 citations into it; #8,816 of 17,773 by trust here, #15,203 by citations
• Algorithms & Complexity — 5 citations into it

Whom Lei Yu trusts overall

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

1. Huan Liu
2. J. Ross Quinlan
3. Manoranjan Dash
4. Ron Kohavi
5. George H. John
6. Avrim Blum
7. Daphne Koller
8. Eric P. Xing
9. Igor Kononenko
10. Sanmay Das

Who trusts Lei Yu overall

1. Huan Liu
2. Verónica Bolón-Canedo
3. Zheng Zhao
4. Noelia Sánchez-Maroño
5. Jiliang Tang
6. Vipin Kumar
7. Salem Alelyani
8. Yun Li
9. Qinghua Hu
10. Zexuan Zhu

Papers from Lei Yu's perspective

Ordered by how strongly the researchers Lei Yu 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. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Toward integrating feature selection algorithms for classification and clustering (2005) — 2,860 citations
• Redundancy based feature selection for microarray data (2004) — 319 citations
• Efficient Feature Selection via Analysis of Relevance and Redundancy (2004) — 2,308 citations
• Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution (2003) — 2,780 citations