A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...
Atharv Kolhar, a staff test automation engineer at Figure AI, says the robotics industry needs a testing philosophy that ...
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 premise is straightforward — we are awash in biological data. The rapid growth of multiomics datasets (genomics, transcriptomics, proteomics, metabolomics, and radiomics) together with ...
Digital technologies are increasingly driving healthcare initiatives to bridge the gap between the haves and have-nots ...
Confidential computing (CC) emerges as an important solution, utilizing hardware-rooted Trusted Execution Environments to ...
As patients are divided into ever more narrowly defined subgroups, the number of individuals available for research shrinks dramatically. While this approach improves personalization, it also creates ...
Abhinav Piratla, an AI security architect, is closing the critical gap in medical device protection. Discover how his ...
Speaking at the first Supreme Court Bar Association National Conference in Bengaluru, Justice BV Nagarathna of the Supreme ...
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