Hyunmin Chae

Reinforcement Learning · 2017

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

Subfields

• Reinforcement Learning — 5 citations into it

Whom Hyunmin Chae trusts overall

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

1. Richard S. Sutton
2. Jan Koutník
3. Chenyi Chen
4. Andrew Barto
5. J. Urgen Schmidhuber
6. Brahim Chaib-draa
7. Mariusz Bojarski

Who trusts Hyunmin Chae overall

1. Sampo Kuutti

Papers from Hyunmin Chae's perspective

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

1. Reinforcement Learning: An Introduction
2. Rectified Linear Units Improve Restricted Boltzmann Machines
3. Gradient-based learning applied to document recognition
4. ImageNet classification with deep convolutional neural networks
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Long Short-Term Memory
7. End to End Learning for Self-Driving Cars
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Autonomous braking system via deep reinforcement learning (2017) — 140 citations