Reliable Federated Learning – Bücher zum Thema Reliable Federated Learning finden und kaufen

Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
Springer Singapore
149.79 € · Hardcover

Distributed Machine Learning Trustworthy Machine Learning Reliable Machine Learning Safe Machine Learning Machine Learning safety Robust Federated Learning Robust Distributed Optimization Byzantine Resilience Byzantine Fault Tolerance in Learning

Today, machine learning algorithms are often distributed across multiple machines to leverage more computing power and more data. However, the use of a distributed framework entails a variety of security threats. In particular, some of the machines may misbehave and jeopardize the learning procedure...

Security and Resilience in Distributed Machine Learning

Kai Li, Xin Yuan, Wei Ni
Springer International Publishing
192.59 € · Hardcover

Reliable Federated Learning Federated Learning Security AI Security and Robustness Federated Learning Attacks Federated Learning Defenses Data Privacy in AI Resilient Federated Learning

This book offers a comprehensive exploration of federated learning (FL), a novel approach to decentralized, privacy-preserving machine learning. This book delves into the resilience and security challenges inherent to FL, such as model poisoning and malicious attacks, that jeopardize system integrit...

Robust Machine Learning

Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
Springer Singapore
139.09 € · eBook

Distributed Machine Learning Trustworthy Machine Learning Reliable Machine Learning Safe Machine Learning Machine Learning safety Robust Federated Learning Robust Distributed Optimization Byzantine Resilience Byzantine Fault Tolerance in Learning

Today, machine learning algorithms are often distributed across multiple machines to leverage more computing power and more data. However, the use of a distributed framework entails a variety of security threats. In particular, some of the machines may misbehave and jeopardize the learning procedure...

Robust Machine Learning

Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
Springer Singapore
149.79 € · Paperback

Distributed Machine Learning Trustworthy Machine Learning Reliable Machine Learning Safe Machine Learning Machine Learning safety Robust Federated Learning Robust Distributed Optimization Byzantine Resilience Byzantine Fault Tolerance in Learning

Today, machine learning algorithms are often distributed across multiple machines to leverage more computing power and more data. However, the use of a distributed framework entails a variety of security threats. In particular, some of the machines may misbehave and jeopardize the learning procedure...

Security and Resilience in Distributed Machine Learning

Kai Li, Xin Yuan, Wei Ni
Springer International Publishing
192.59 € · eBook

Reliable Federated Learning Federated Learning Security AI Security and Robustness Federated Learning Attacks Federated Learning Defenses Data Privacy in AI Resilient Federated Learning

This book offers a comprehensive exploration of federated learning (FL), a novel approach to decentralized, privacy-preserving machine learning. This book delves into the resilience and security challenges inherent to FL, such as model poisoning and malicious attacks, that jeopardize system integrit...

AI for Clinical Applications

Springer International Publishing
69.54 € · eBook

Regulatory science medical AI evaluation post-market monitoring AI in healthcare deployment responsible AI reliable AI responsible AI deployment global regulatory alignment AI performance monitoring robust AI evaluation frameworks Federated learning Distributed learning Collaborative learning Optimization methods Data heterogeneity

This book constitutes the proceedings of the First International Workshop on Agentic AI for Medicine, Agentic AI 2025, the First International Workshop on Clinical-Driven Robotics and Embodied AI Technology, CREATE 2025, and the First International Workshop on Multimodal Large Language Models in Cli...

AI for Clinical Applications

Springer International Publishing
70.61 € · Paperback

Regulatory science medical AI evaluation post-market monitoring AI in healthcare deployment responsible AI reliable AI responsible AI deployment global regulatory alignment AI performance monitoring robust AI evaluation frameworks Federated learning Distributed learning Collaborative learning Optimization methods Data heterogeneity

This book constitutes the proceedings of the First International Workshop on Agentic AI for Medicine, Agentic AI 2025, the First International Workshop on Clinical-Driven Robotics and Embodied AI Technology, CREATE 2025, and the First International Workshop on Multimodal Large Language Models in Cli...

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