IEEE

Trends and Challenges in Computing-in-Memory for Neural Network Model: A Review From Device Design to Application-Side Optimization

Abstract: Neural network models have been widely used in various fields as the main way to solve problems in the current artificial intelligence (AI) field. Efficient execution of neural network ...
techxplore

Overparameterized neural networks: Feature learning precedes overfitting, research finds

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, structureless data. Yet when trained on datasets with structure, they learn the ...
Bleeping Computer

Hackers are exploiting ArrayOS AG VPN flaw to plant webshells

Threat actors have been exploiting a command injection vulnerability in Array AG Series VPN devices to plant webshells and create rogue users. Array Networks fixed the vulnerability in a May security ...
IEEE

Comprehensive Design Space Exploration for Graph Neural Network Aggregation on GPUs

Abstract: Graph neural networks (GNNs) have become the state-of-the-art technology for extracting and predicting data representations on graphs. With increasing demand to accelerate GNN computations, ...