G. Subbaraj

Artificial Intelligence · 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

• Artificial Intelligence — 39 citations into it
• Reinforcement Learning — 29 citations into it
• Management Science and Operations Research — 15 citations into it

Whom G. Subbaraj trusts overall

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

1. Richard S. Sutton

Papers from G. Subbaraj's perspective

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

1. Reinforcement Learning: An Introduction
2. Policy Gradient Methods for Reinforcement Learning with Function Approximation
3. Overcoming catastrophic forgetting in neural networks
4. Near-Optimal Reinforcement Learning in Polynomial Time
5. Progressive Neural Networks
6. Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem
7. Near-optimal Regret Bounds for Reinforcement Learning
8. A Reinforcement Learning Method for Maximizing Undiscounted Rewards
9. On the role of tracking in stationary environments
10. Progress & Compress: A scalable framework for continual learning

Their papers

• Continual Learning In Environments With Polynomial Mixing Times (2021) — 17 citations