Paul Weng

Artificial Intelligence · 2013–2023

A researcher in the Science corpus: 7 papers; trusts 42 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 63 citations into it
• Reinforcement Learning — 39 citations into it
• Management Science and Operations Research — 20 citations into it
• Information Systems — 16 citations into it
• Computer Networks and Communications — 11 citations into it
• Computational Theory and Mathematics — 10 citations into it
• Statistics and Probability — 9 citations into it
• Control and Systems Engineering — 6 citations into it

Whom Paul Weng trusts overall

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

1. Ronald J. Williams
2. Csaba Szepesvari
3. Oded Maron
4. Richard S. Sutton
5. Yufan Zhao
6. Johannes Fürnkranz
7. Pieter Abbeel
8. Martin L. Puterman
9. Peter Auer
10. Riad Akrour

Who trusts Paul Weng overall

1. Khimya Khetarpal
2. Pablo Hernandez-Leal
3. Yusen Zhan
4. Erwan Lecarpentier
5. Christian Wirth

Papers from Paul Weng's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Attention is All you Need (Neural Information Processing Systems)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Reinforcement Learning: An Introduction
5. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet: A large-scale hierarchical image database

Their papers

• Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm (2014) — 73 citations
• Solving Hidden-Semi-Markov-Mode Markov Decision Problems (2014) — 17 citations
• Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems (2019) — 362 citations
• A Survey of Reinforcement Learning from Human Feedback (2023) — 338 citations
• Sequential Decision-Making under Non-stationary Environments via Sequential Change-point Detection (2014) — 34 citations
• Teacher-Student Framework: a Reinforcement Learning Approach (2014) — 68 citations
• Preference-based Evolutionary Direct Policy Search (2013) — 22 citations