How modern infostealers target macOS systems, leverage Python‑based stealers, and abuse trusted platforms and utilities to ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
I'll explore data-related challenges, the increasing importance of a robust data strategy and considerations for businesses ...
Condensed-matter physics and materials science have a silo problem. Although researchers in these fields have access to vast amounts of data – from experimental records of crystal structures and ...
Abstract: In federated learning, non-independently and non-identically distributed heterogeneous data on the clients can limit both the convergence speed and model utility of federated learning, and ...
Implementation of Federated Learning Algorithms for Non Independent and Identically Distributed Data
Abstract: Federated Learning (FL) has emerged as a transformative approach for training machine learning models across decentralized data sources while preserving privacy. This study evaluates the ...
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