Triangular Dropout: Variable Network Width without Retraining

no code implementations • 29 Sep 2021 • Edward W Staley, Corban G Rivera, Neil Joshi

One of the most fundamental design choices in neural networks is layer width: it affects the capacity of what a network can learn and determines the complexity of the solution.

Reinforcement Learning (RL)