In this tutorial, we present an advanced, hands-on tutorial that demonstrates how we use Qrisp to build and execute non-trivial quantum algorithms. We walk through core Qrisp abstractions for quantum ...

As one of the important statistical methods, quantile regression (QR) extends traditional regression analysis. In QR, various quantiles of the response variable are modeled as linear functions of the ...

Abstract: Several interesting problems in multirobot systems can be cast in the framework of distributed optimization. Examples include multirobot task allocation, vehicle routing, target protection, ...

This repository contains an implementation of distributed matching algorithms for IoT-based resource allocation. The project simulates a complex environment of users, access points, and cloudlets to ...

In a milestone that brings quantum computing tangibly closer to large-scale practical use, scientists at Oxford University Physics have demonstrated the first instance of distributed quantum computing ...

We analyze several generic proximal splitting algorithms well suited for large-scale convex nonsmooth optimization. We derive sublinear and linear convergence results with new rates on the function ...

This repository contains the experiments conducted in the paper: "Distributed Clustering via LSH Based Data Partitioning" (ICML 2018) with synthetic data. This implementation is not a distributed ...