SVHN

Researchers propose a loss-aware feature-map pruning framework for convolutional neural networks that uses multi-armed bandits (UCB1 and Thompson Sampling) to identify and remove redundant feature map…

Researchers introduced Pre-Warm, a zero-training-cost method for data-conditioned initialization of the first convolutional layer in CNNs. The technique clusters patches from a single training batch t…

Researchers have developed a tensor similarity method that can detect changes in neural network behavior, such as backdoor attacks, by comparing the weight-space structure of models rather than just t…