We introduce MNISQ, the first large-scale dataset for both quantum and classical machine learning during the NISQ era, containing 4.95 million circuits of 10 qubits constructed with up to 100 ...

This tutorial tries to do what most Most Machine Learning tutorials available online do not. It is not a 30 minute tutorial which teaches you how to "Train your own neural network" or "Learn deep ...

Secret Key,Public Key,Communication Overhead,Smart Contracts,Threat Model,Internet Of Things,Hash Function,Federated Learning,Computational Overhead,Security ...

Application of deep convolutional spiking neural networks (SNNs) to artificial intelligence (AI) tasks has recently gained a lot of interest since SNNs are hardware-friendly and energy-efficient.

The computational cost of deep neural networks presents challenges to broadly deploying these algorithms. Low-power and embedded neuromorphic processors offer potentially dramatic performance-per-watt ...

This tutorial was presented at [Trevor Hastie](http://www-stat.stanford.edu/~hastie) and [Rob Tibshirani](http://www-stat.stanford.edu/~tibs)'s [Statistical Learning ...

Many believe a Google search can identify most of the information available on the Internet on a given subject. But there is an entire online world – a massive one – beyond the reach of Google or any ...