Lequn Wang

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 13 citations into it
• Management Science and Operations Research — 8 citations into it
• Reinforcement Learning — 8 citations into it
• Statistics and Probability — 7 citations into it

Whom Lequn Wang trusts overall

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

1. Thorsten Joachims
2. Adith Swaminathan
3. J. Langford
4. James M. Robins
5. Subir Ghosh
6. Miroslav Dud'ik
7. Alina Beygelzimer
8. Alekh Agarwal
9. Philip S. Thomas
10. H. Bang

Who trusts Lequn Wang overall

1. Noveen Sachdeva
2. Yuta Saito

Papers from Lequn Wang's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Reinforcement Learning: An Introduction
3. Gradient-based learning applied to document recognition
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
7. Attention is All you Need (Neural Information Processing Systems)
8. Doubly Robust Policy Evaluation and Learning
9. Long Short-Term Memory
10. Human-level control through deep reinforcement learning

Their papers

• CAB: Continuous Adaptive Blending for Policy Evaluation and Learning (2019) — 91 citations