Fatima Davelouis

On the Interplay Between Sparsity and Training in Deep Reinforcement Learning

2025 · arXiv (Cornell University)

We study the benefits of different sparse architectures for deep reinforcement learning. In particular, we focus on image-based domains where spatially-biased and fully-connected architectures are common. Using these and several other architectures of equal capacity, …