Spiking neural networks (SNNs) represent a promising approach to developing artificial neural networks that are both energy-efficient and biologically plausible.

Most existing neural architecture search (NAS) algorithms are dedicated to and evaluated bythedownstream tasks, e.g.,image classification incomputer vision.

In theory, the techniques can speed up matrix operations, however,inpractice, theyare not fastenough.

In theory, the techniques can speed up matrix operations, however,inpractice, theyare not fastenough.

Clustering is a fundamental problem in unsupervised learning with several practical applications. In clustering, one is interested in partitioning elements into different groups (i.e.

There has been much interest in recent years in the problem of dueling bandits, where on each round the learner plays a pair of arms and receives as feedback the outcome of a relative pairwise comparison between them.

We give partial answers to these questions based on extensive empirical evaluation.