Multi-scale models provide a simple yet powerful framework for approximating and extending functions defined over grid-based or scattered datasets. In this talk, we focus on multi-scale kernel methods ...

Are two sets of data genuinely different, or is it because of randomness? This question, known as the two-sample testing problem, becomes notoriously difficult in modern datasets, because they are ...

Quantum information scientists have introduced a new method for machine-learning classifications in quantum computing. The non-linear quantum kernels in a quantum binary classifier provide new ...

As AI continues to reshape the way developers build applications, Microsoft's Semantic Kernel is emerging as a powerful tool for integrating AI-driven capabilities into existing codebases -- without ...