Kernel functions are vital ingredients of several machine learning (ML) algorithms but often incur substantial memory and computational costs. We introduce an approach to kernel approximation in ML ...

In the machine learning world, the sizes of artificial neural networks — and their outsize successes — are creating conceptual conundrums. When a network named AlexNet won an annual image recognition ...

Quantum algorithms have become a popular research domain in recent times for discovering quantum-enhanced solutions in machine learning applications. Quantum kernels are one of the directions that ...