Bo Liu
Reinforcement Learning · with Mahadevan · 2012–2020
A researcher in the Science corpus: 8 papers; trusts 175 researchers and is trusted by 34 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 197 citations into it; #805 of 2,242 by trust here, #1,371 by citations
- Artificial Intelligence — 149 citations into it; #5,102 of 35,345 by trust here, #9,465 by citations
- Optimization & Training — 71 citations into it; #1,455 of 2,601 by trust here, #1,638 by citations
- Management Science and Operations Research — 55 citations into it; #7,576 of 11,946 by trust here, #7,262 by citations
- Computational Theory and Mathematics — 51 citations into it; #2,661 of 12,182 by trust here, #3,033 by citations
- Computational Mechanics — 21 citations into it; #2,042 of 10,001 by trust here, #3,029 by citations
- Electrical and Electronic Engineering — 21 citations into it
- Mathematical Optimization — 20 citations into it
Whom Bo Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- Dimitri P. Bertsekas
- Hamid Reza Maei
- Csaba Szepesvari
- J. Kolter
- Andrew Barto
- Leemon C. Baird III
- Yurii E. Nesterov
- Sridhar Mahadevan
- Geoffrey E. Hinton
Who trusts Bo Liu overall
- Shangtong Zhang
- Bo Dai
- Ziyang Tang
- Adam White
- Ofir Nachum
- Huizhen Yu
- Lihong Li
- Sridhar Mahadevan
- Mohammad Ghavamzadeh
- Martha White
Papers from Bo Liu's perspective
Ordered by how strongly the researchers Bo Liu trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Reinforcement Learning: An Introduction
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Finite-Sample Analysis of Proximal Gradient TD Algorithms (2015) — 164 citations
- GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values (2020) — 110 citations
- Regularized Off-Policy TD-Learning (2012) — 65 citations
- Proximal Reinforcement Learning: A New Theory of Sequential Decision Making in Primal-Dual Spaces (2014) — 73 citations
- Sparse Q-learning with Mirror Descent (2012) — 41 citations
- Provably Convergent Off-Policy Actor-Critic with Function Approximation (2019) — 8 citations
- QUOTA: The Quantile Option Architecture for Reinforcement Learning (2018) — 33 citations
- Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation (2019) — 60 citations