Parikshit Hegde

Reinforcement Learning · 2017

A researcher in the Science corpus: 1 paper; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 17 citations into it
• Artificial Intelligence — 15 citations into it
• Electrical and Electronic Engineering — 5 citations into it

Whom Parikshit Hegde trusts overall

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

1. Richard S. Sutton
2. Volodymyr Mnih
3. Burr Settles
4. Yann LeCun
5. Yoshua Bengio
6. Geoffrey E. Hinton
7. Peter Auer
8. Aravind S. Lakshminarayanan
9. Jimmy Ba
10. Emilio Parisotto

Who trusts Parikshit Hegde overall

1. Michael Crawshaw
2. Matthew Riemer

Papers from Parikshit Hegde's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Asynchronous Methods for Deep Reinforcement Learning
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Learning to Multi-Task by Active Sampling (2017) — 40 citations