Regina Padmanabhan

Reinforcement Learning · 2014–2017

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 8 citations into it
• Artificial Intelligence — 5 citations into it

Whom Regina Padmanabhan trusts overall

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

1. Dimitri P. Bertsekas
2. Richard S. Sutton
3. Andrew Barto
4. Wassim M. Haddad

Who trusts Regina Padmanabhan overall

1. Chao Yu
2. Jiming Liu
3. Shamim Nemati

Papers from Regina Padmanabhan's perspective

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

1. Gradient-based learning applied to document recognition
2. Reinforcement Learning: An Introduction
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Nonlinear Dynamical Systems and Control: A Lyapunov-Based Approach
6. Long Short-Term Memory
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
9. Linear Least-Squares algorithms for temporal difference learning
10. Et al

Their papers

• Reinforcement learning-based control of drug dosing for cancer chemotherapy treatment. (2017) — 117 citations
• Closed-loop control of anesthesia and mean arterial pressure using reinforcement learning (2014) — 106 citations