Daniele Giardino

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 Daniele Giardino trusts overall

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

1. Richard S. Sutton

Papers from Daniele Giardino's perspective

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

1. Reinforcement Learning: An Introduction
2. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
3. Asynchronous Methods for Deep Reinforcement Learning
4. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
5. Human-level control through deep reinforcement learning
6. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
7. Curriculum learning
8. Trust Region Policy Optimization (International Conference on Machine Learning)
9. ImageNet classification with deep convolutional neural networks
10. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning

Their papers

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