Tag: federated learning
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Data-Free Client Contribution Estimation in Federated Learning
Discover data-free methods using gradient von Neumann entropy for accurate client contribution estimation in federated learning while ensuring privacy.
GradsSharding: Scalable Serverless Federated Learning
Discover GradsSharding, a serverless federated learning method that shards gradients for scalable, memory-efficient AI model aggregation.
Sherpa.ai Multi-Party Privacy-Preserving Entity Alignment
Discover Sherpa.ai's multi-party protocol for privacy-preserving entity alignment without intersection disclosure, enabling secure, noisy data matching.
DP-FlogTinyLLM: Private Federated Log Anomaly Detection
Discover DP-FlogTinyLLM, a privacy-preserving federated learning framework using Tiny LLMs for efficient and secure log anomaly detection.
FedProxy: Advanced Federated Fine-Tuning for Large Language Models
Discover FedProxy, a cutting-edge framework enabling secure, efficient federated fine-tuning of LLMs with privacy and performance across diverse data.