Yu Lu

Reinforcement Learning · with Li · 2017

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

Subfields

• Reinforcement Learning — 10 citations into it; #1,860 of 2,242 by trust here, #2,125 by citations
• Artificial Intelligence — 9 citations into it
• Management Science and Operations Research — 8 citations into it; #9,041 of 11,946 by trust here, #9,931 by citations
• Statistics and Probability — 6 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Yu Lu trusts overall

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

1. Peter Auer
2. Eric R. Ziegel
3. Lihong Li
4. Roman Vershynin
5. Lawrence D. Brown
6. Olivier Chapelle
7. Nicolò Cesa-Bianchi
8. Daniel Russo
9. Yasin Abbasi-Yadkori
10. J. Langford

Who trusts Yu Lu overall

1. Aadirupa Saha

Papers from Yu Lu's perspective

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

1. Asymptotically efficient adaptive allocation rules
2. Using Confidence Bounds for Exploitation-Exploration Trade-offs
3. A contextual-bandit approach to personalized news article recommendation
4. Finite-time Analysis of the Multiarmed Bandit Problem
5. ON THE LIKELIHOOD THAT ONE UNKNOWN PROBABILITY EXCEEDS ANOTHER IN VIEW OF THE EVIDENCE OF TWO SAMPLES
6. Gradient-based learning applied to document recognition
7. ImageNet classification with deep convolutional neural networks
8. Contextual Bandits with Linear Payoff Functions
9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
10. The Nonstochastic Multiarmed Bandit Problem

Their papers

• Provable Optimal Algorithms for Generalized Linear Contextual Bandits (2017) — 86 citations