Abstract: We propose an effective approach toward implementing personalized federated learning at the edge of wireless networks. The scheme employs a bi-level optimization framework to personalize the ...
Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
Learn about DenseNet, one of the most powerful deep learning architectures, in this beginner-friendly tutorial. Understand its structure, advantages, and how it’s used in real-world AI applications.
According to DeepLearning.AI (@DeepLearningAI), the new PyTorch for Deep Learning Professional Certificate, led by Laurence Moroney, provides in-depth, practical training on building, optimizing, and ...
Asynchronous Federated Learning with non-convex client objective functions and heterogeneous dataset
Abstract: Federated Learning is a distributed machine learning paradigm that enables model training across decentralized devices holding local data, thereby preserving data privacy and reducing the ...
ABSTRACT: Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management. Conventional asset pricing models, such as the Fama-French three-factor ...
Vikram Gupta is Chief Product Officer, SVP & GM of the IoT Processor Business Division at Synaptics, a leading EdgeAI semiconductor company. In my previous articles, I explored how the rapid growth of ...
Reinforcement learning has emerged as a powerful approach to fine-tune large language models (LLMs) for more intelligent behavior. These models are already capable of performing a wide range of tasks, ...
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