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 ...

This project implements a neural network from scratch to classify handwritten digits using the MNIST dataset. The neural network is built using Python and utilizes libraries such as NumPy and ...

What if you could turn Excel into a powerhouse for advanced data analysis and automation in just a few clicks? Imagine effortlessly cleaning messy datasets, running complex calculations, or generating ...

1 Very Large Scale Integration Laboratory, Department of Electronics Engineering, Politecnico di Torino, Torino, Italy 2 eBrain Lab, Division of Engineering, New York University, Abu Dhabi, United ...

This repository contains the technical implementation of the paper Statistical Test-based Adversarial Client Detection in Federated Learning under Poisoning Attacks, as well as proof of its results.

In view of the growing volume of data, there is a notable research focus on hardware that offers high computational performance with low power consumption. Notably, neuromorphic computing, ...

In this tutorial, we demonstrate how to efficiently fine-tune the Llama-2 7B Chat model for Python code generation using advanced techniques such as QLoRA, gradient checkpointing, and supervised ...

Harvard University announced Thursday it’s releasing a high-quality dataset of nearly 1 million public-domain books that could be used by anyone to train large language models and other AI tools. The ...

This paper presents a new dataset of monetary policy shocks for 21 advanced economies and 8 emerging markets from 2000-2022. We use daily changes in interest rate swap rates around central bank ...