Sulin Liu

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 29 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 32 citations into it; #22,655 of 35,345 by trust here, #20,836 by citations
• Representation & Self-Supervised Learning — 14 citations into it
• Computational Mechanics — 12 citations into it; #6,263 of 10,001 by trust here, #5,813 by citations
• Computer Networks and Communications — 12 citations into it
• Optimization & Training — 11 citations into it
• Safety, Robustness & Interpretability — 11 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it

Whom Sulin Liu trusts overall

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

1. Theodoros Evgeniou
2. Tong Zhang
3. Peter Richtárik
4. Yu Zhang
5. Shai Shalev-Shwartz
6. Massimiliano Pontil
7. Yu Zhang
8. Rie Kubota Ando
9. Ali Rahimi
10. Laurent Jacob

Who trusts Sulin Liu overall

1. Virginia Smith
2. Sebastian Caldas
3. Filip Hanzely
4. Mohammad Rostami
5. Mengchen Zhao
6. Ameet Talwalkar
7. Chao-Kai Chiang
8. Slavomír Hanzely
9. Bo An
10. Arghya Pal

Papers from Sulin Liu's perspective

Ordered by how strongly the researchers Sulin Liu 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. 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

• Distributed Multi-Task Relationship Learning (2017) — 75 citations
• Data Poisoning Attacks on Multi-Task Relationship Learning (2018) — 46 citations