Linli Xu

Artificial Intelligence · 2004–2021

A researcher in the Science corpus: 6 papers; trusts 117 researchers and is trusted by 81 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 83 citations into it; #25,925 of 35,345 by trust here, #23,731 by citations
• Computer Vision and Pattern Recognition — 58 citations into it; #4,484 of 21,575 by trust here, #5,205 by citations
• Natural Language Processing — 48 citations into it
• Optimization & Training — 17 citations into it; #1,611 of 2,601 by trust here, #1,986 by citations
• Representation & Self-Supervised Learning — 14 citations into it; #901 of 3,145 by trust here, #1,561 by citations
• Computational Mechanics — 9 citations into it
• Statistical Learning Theory — 8 citations into it
• Generative Models — 6 citations into it

Whom Linli Xu trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Peter L. Bartlett
4. Thorsten Joachims
5. Bernhard Schölkopf
6. Andrew Y. Ng
7. Alex Krizhevsky
8. Kaiming He
9. Diederik P. Kingma
10. Yann LeCun

Who trusts Linli Xu overall

1. Armand Joulin
2. Francis R. Bach
3. Xiaogang Wang
4. Piotr Bojanowski
5. Ronan Collobert
6. J. Paul Brooks
7. Kyunghyun Cho
8. Jean-Baptiste Alayrac
9. Xiao-Lei Zhang
10. Ivan Laptev

Papers from Linli Xu's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Image Denoising and Inpainting with Deep Neural Networks (2012) — 1,465 citations
• Adaptive Adapters: An Efficient Way to Incorporate BERT Into Neural Machine Translation (2021) — 26 citations
• Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input (2018) — 133 citations
• Robust Dynamic Trajectory Regression on Road Networks: A Multi-task Learning Framework (2014) — 8 citations
• Robust Support Vector Machine Training via Convex Outlier Ablation (2006) — 177 citations
• Maximum Margin Clustering (2004) — 528 citations