In the realm of machine learning, the performance of a model often hinges on the optimal selection of hyperparameters. These parameters, which lie beyond the control of the learning algorithm, dictate ...

FiGS, is a probabilistic approach to channel regularization that we introduced in Fine-Grained Stochastic Architecture Search. It outperforms our previous regularizers and can be used as either a ...