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 ...

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 ...

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 ...

The field of orofacial medicine increasingly recognizes the temporomandibular joint (TMJ) as a complex anatomical and functional unit whose disorders can ...

Confidential computing (CC) emerges as an important solution, utilizing hardware-rooted Trusted Execution Environments to ...

The energy sector is becoming a highly connected cyber-physical ecosystem in which distributed energy resources, electric ...

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?

Our paper about the robust FL algorithms evaluation with a new algorithm has been accepted by NeurIPS 2025, please check our FedGPS. In the open-source code of FedGPS we provide a clearer codebase for ...

Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...

Together AI, which specializes in open-source artificial intelligence models, is now worth more than $8 billion. By Niko Gallogly In recent weeks, two related developments have threatened to reshape ...

While Anthropic is dealing with a government-ordered suspension of its newest Fable and Mythos models, Microsoft is emphasizing a more enterprise-ready Claude path through Microsoft Foundry.