3 papers
cs.CV2020
Neural gradients are near-lognormal: improved quantized and sparse training
Brian Chmiel, Liad Ben-Uri, Moran Shkolnik +3
While training can mostly be accelerated by reducing the time needed to propagate neural gradients back throughout the model, most previous works focus on the quantization/pruning…
cs.LG2020
Robust Quantization: One Model to Rule Them All
Moran Shkolnik, Brian Chmiel, Ron Banner +4
Neural network quantization methods often involve simulating the quantization process during training, making the trained model highly dependent on the target bit-width and precise…
cs.CV2019
Thanks for Nothing: Predicting Zero-Valued Activations with Lightweight Convolutional Neural Networks
Gil Shomron, Ron Banner, Moran Shkolnik +1
Convolutional neural networks (CNNs) introduce state-of-the-art results for various tasks with the price of high computational demands. Inspired by the observation that spatial cor…