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RT-kNNS Unbound: Using RT Cores to Accelerate Unrestricted Neighbor Search
The problem of identifying the k-Nearest Neighbors (kNNS) of a point has proven to be very useful both as a standalone application and as a subroutine in larger applications.
Quantum Computing Methods for Supervised Learning
However, owing to its roots in quantum mechanics, research in this field has so far been confined within the purview of the physics community, and most work is not easily accessible to researchers from other disciplines.
Survey of Personalization Techniques for Federated Learning
Federated learning enables machine learning models to learn from private decentralized data without compromising privacy.
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