Summary Background The Global Burden of Diseases, Injuries, and Risk Factors Study
(GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor …

An increasing number of machine learning tasks require dealing with large graph datasets,
which capture rich and complex relationship among potentially billions of elements. Graph …

Emerging graph neural networks (GNNs) have extended the successes of deep learning
techniques against datasets like images and texts to more complex graph-structured data …

Graph neural networks (GNNs) emerge as a powerful approach to process non-euclidean
data structures and have been proved powerful in various application domains such as …

We consider a basic content distribution scenario consisting of a single origin server
connected through a shared bottleneck link to a number of users each equipped with a …

During the last 15 years online algorithms have received considerable research interest. In
this survey we give an introduction to the competitive analysis of online algorithms and …

Over the past twelve years, online algorithms have received considerable research interest.
Online problems had been investigated already in the seventies and early eighties but an …

The design and analysis of algorithms deals with extracting certain information from
instances of computational problems. In a way, this information is “hidden” in the instances …

We revisit the question of the effectiveness of the popular LRU cache eviction policy versus
the FIFO heuristic which attempts to give an LRU like behavior. Several past works have …

Emerging graph neural networks (GNNs) have extended the successes of deep learning
techniques against datasets like images and texts to more complex graph-structured data …