ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

Abstract: Deep neural networks often suffer from poor performance or even training failure due to the ill-conditioned problem, the vanishing/exploding gradient problem, and the saddle point problem.

There are things we expect from high temperatures, like sweat, increased irritability. There are things, however, that we just don't expect to hear about during a heat wave, like exploding soda cans ...

GameSpot may get a commission from retail offers. A new Helldivers 2 patch has gone live, and amongst numerous tweaks, a fix to stop mechs from exploding is quite welcome. Mechs were only recently ...

Machine Learning Practical - Coursework 2 Report: Analysing problems with the VGG deep neural network architectures (with 8 and 38 hidden layers) on the CIFAR100 dataset by monitoring gradient flow ...

Abstract: In this letter, we propose a bio-inspired derivative-free optimization algorithm capable of minimizing objective functions with vanishing or exploding gradients. The proposed method searches ...

Machine learning is on track to consume all the energy being supplied, a model that is costly, inefficient, and unsustainable. To a large extent, this is because the field is new, exciting, and ...

Researchers from MIT and Facebook AI have developed projUNN, an effective method for training deep networks using unitary matrices. The projUNN method includes two variants, projUNN-D and projUNN-T, ...