IEEE

SWOSBC: A Novel Optimizer for Learning Convolutional Neural Network

Abstract: Deep Neural Networks (DNNs) that aim to maximize accuracy and decrease loss can be trained using optimization algorithms. One of the most significant fields of research is the creation of an ...
GitHub

Can not fetch mnist data set

File "/home/nonroot/condaforge_src/envs/torch/lib/python3.12/site-packages/torch/multiprocessing/spawn.py", line 364, in spawn return start_processes(fn, args, nprocs ...
IEEE

APR-FL: Defending Against Hidden Backdoor Attacks With Adaptive Parameter Replacement

Abstract: Federated learning (FL) has become a key technology for achieving efficient and reliable edge AI decision-making in consumer electronics devices. However, its application in open network ...
marktechpost

On-Chip Implementation of Backpropagation for Spiking Neural Networks on Neuromorphic Hardware

Natural neural systems have inspired innovations in machine learning and neuromorphic circuits designed for energy-efficient data processing. However, implementing the backpropagation algorithm, a ...
GitHub

introduction_to_mnist.ipynb

"In the following tutorials, we are going to use the MNIST database of handwritten digits. MNIST is a simple computer vision dataset of handwritten digits. It has 60,000 training examles and 10,000 ...