Tag: Model Optimization

AI Machine Learning & Data Science Research

How to speedup 31*31 conv 10 times

MegEngine Teams propose large-kernel convolution optimization strategy, speeding up 31*31 convolutional neural networks 10 times.

AI Machine Learning & Data Science Research

CMU, UT Austin & Facebook’s CNN Layer Width Optimization Strategies Achieve 320x Overhead Reduction

Researchers from Carnegie Mellon University, the University of Texas at Austin and Facebook AI propose a novel paradigm to optimize widths for each CNN layer. The method is compatible across various width optimization algorithms and networks and achieves up to a 320x reduction in width optimization overhead without compromising top-1 accuracy on ImageNet.