37 citations · 115 across the 11 of their papers we have counts for
4 papers · 1 filter
Unified CNNs and transformers underlying learning mechanism reveals multi-head attention modus vivendi
Ella Koresh, Ronit D. Gross, Yuval Meir +3
Convolutional neural networks (CNNs) evaluate short-range correlations in input images which progress along the layers, whereas vision transformer (ViT) architectures evaluate long…
Advanced deep architecture pruning using single filter performance
Yarden Tzach, Yuval Meir, Ronit D. Gross +3
Pruning the parameters and structure of neural networks reduces the computational complexity, energy consumption, and latency during inference. Recently, a novel underlying mechani…
Efficient shallow learning as an alternative to deep learning
Yuval Meir, Ofek Tevet, Yarden Tzach +3
The realization of complex classification tasks requires training of deep learning (DL) architectures consisting of tens or even hundreds of convolutional and fully connected hidde…
Power-law Scaling to Assist with Key Challenges in Artificial Intelligence
Yuval Meir, Shira Sardi, Shiri Hodassman +4
Power-law scaling, a central concept in critical phenomena, is found to be useful in deep learning, where optimized test errors on handwritten digit examples converge as a power-la…