Quantile regression is a method of fundamental importance. How to efficiently conduct quantile regression for a large dataset on a distributed system is of great importance. We show that the popula…
Abstract–Understanding why extreme events occur is often of major scientific interest in many fields. The occurrence of these events naturally depends on explanatory variables, but there is a sev…
We establish a high-dimensional statistical learning framework for individualized asset allocation. Our proposed methodology addresses continuous-action decision-making with a large number of chara…
In this article, we propose a model-free conditional feature screening method with false discovery rate (FDR) control for ultra-high dimensional data. The proposed method is built upon a new measur…
It is easy to verify that if A is a doubly stochastic matrix, then both its normal equations AAT and ATA are also doubly stochastic, but the reciprocal is not true. In this paper, we introduce and …
We study a server routing-scheduling problem in a distributed queueing system, where the system consists of multiple queues at different locations. In a distributed queueing system, servers are sha…
Corporate probability of default (PD) prediction is vitally important for risk management and asset pricing. In search of accurate PD prediction, we propose a flexible yet easy-to-interpret default…
This article seeks to explain why some popular neighbourhoods in Buenos Aires have responded more effectively than others to COVID-19. It compares actions that took place between March and October …
An advanced light source at blue-green waveband is the key to improve the link-distance and communication performance of an underwater wireless optical communication (UWOC) system. This work presen…
In this article a fibre free-space fibre link that allows a quantum key distribution (QKD) signal and high-speed data to be transmitted in a single optical beam is presented. This setup has the pot…