L. Di Nunzio

Reinforcement Learning · 2021

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 34 citations into it
• Artificial Intelligence — 29 citations into it

Whom L. Di Nunzio trusts overall

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

1. Richard S. Sutton
2. Ben J. A. Kröse
3. Yoshua Bengio
4. Sergey Ioffe
5. Geoffrey E. Hinton
6. Ronald J. Williams
7. Jakob N. Foerster

Papers from L. Di Nunzio's perspective

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

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

Their papers

• Multi-Agent Reinforcement Learning: A Review of Challenges and Applications (2021) — 426 citations