The main goal of this paper is to survey the influential research of distributed learning
technologies playing a key role in the 6G world. Upcoming 6G technology is expected to …

Transformer models have emerged as the state-of-the-art in many natural language
processing and computer vision applications due to their capability of attending to longer …

Dynamic Sparse Training (DST) methods achieve state-of-the-art results in sparse neural
network training, matching the generalization of dense models while enabling sparse …

Sparsity has long been a theoretical and practical signal property in applied mathematics
and is utilized as a crucial concept in signal/image processing applications such as …

Recently, the layer-wise N: M fine-grained sparse neural network algorithm (ie, every M-
weights contains N non-zero values) has attracted tremendous attention, as it can effectively …