Tingting Zhao

Reinforcement Learning · with Mori · 2013

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 13 citations into it
• Artificial Intelligence — 6 citations into it

Whom Tingting Zhao trusts overall

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

1. Richard S. Sutton
2. Ronald J. Williams
3. Sham M. Kakade
4. Jan Peters
5. Masashi Sugiyama
6. Geoffrey E. Hinton
7. Peter S. Dayan
8. Marc Peter Deisenroth
9. Andrew Barto
10. Michail G. Lagoudakis

Papers from Tingting Zhao's perspective

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

1. Reinforcement Learning: An Introduction
2. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Policy Gradient Methods for Reinforcement Learning with Function Approximation
6. Gradient-based learning applied to document recognition
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Model-Based Policy Gradients with Parameter-Based Exploration by Least-Squares Conditional Density Estimation (2013) — 26 citations