Basque startup Sherpa.ai has raised $18m from US investor Forgepoint for federated-learning AI that trains models without sharing sensitive data.
Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...
Abstract: Federated learning enables participants to collaboratively train a global model through distributed training without sharing raw data. However, this distributed training is vulnerable to ...
Abstract: Recent years have witnessed a huge demand for artificial intelligence and machine learning applications in wireless edge networks to assist individuals with real-time services. Federated ...
The energy sector is becoming a highly connected cyber-physical ecosystem in which distributed energy resources, electric ...
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Data Scientist Ke Zhang’s Research Explores Homomorphic Encryption for Privacy-Preserving Marketing
A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...
The premise is straightforward — we are awash in biological data. The rapid growth of multiomics datasets (genomics, transcriptomics, proteomics, metabolomics, and radiomics) together with ...
Atharv Kolhar, a staff test automation engineer at Figure AI, says the robotics industry needs a testing philosophy that ...
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