Christopher Lo

Artificial Intelligence · 2016

A researcher in the Science corpus: 2 papers; trusts 20 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 40 citations into it; #9,447 of 35,345 by trust here, #19,018 by citations
• Management Science and Operations Research — 21 citations into it; #2,304 of 11,946 by trust here, #4,430 by citations
• Reinforcement Learning — 18 citations into it; #807 of 2,242 by trust here, #1,609 by citations
• Natural Language Processing — 13 citations into it; #2,904 of 5,688 by trust here, #4,793 by citations
• Optimization & Training — 13 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it
• Statistics and Probability — 6 citations into it
• Computer Networks and Communications — 5 citations into it

Whom Christopher Lo trusts overall

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

1. Thorsten Joachims
2. David Chiang
3. Alekh Agarwal
4. Franz Joseph Och
5. Shai Shalev-Shwartz
6. Edward L. Ionides
7. Boris Polyak
8. Zhifei Li
9. Ilya Sutskever
10. Geoffrey E. Hinton

Who trusts Christopher Lo overall

1. Julia Kreutzer
2. Yang Gao
3. Artem Sokolov
4. Stefan Riezler
5. Christian M. Meyer
6. Iryna Gurevych

Papers from Christopher Lo's perspective

Ordered by how strongly the researchers Christopher Lo 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. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Learning Structured Predictors from Bandit Feedback for Interactive NLP (2016) — 34 citations
• Stochastic Structured Prediction under Bandit Feedback (2016) — 31 citations