The frequency distribution of words has been a key object of study in statistical linguistics for
the past 70 years. This distribution approximately follows a simple mathematical form known …

Multi-access edge computing (MEC) has recently been proposed to aid mobile end devices
in providing compute-and data-intensive services with low latency. Growing service …

Federated learning (FL) is a distributed deep learning method that enables multiple
participants, such as mobile and IoT devices, to contribute a neural network while their …

In order to evaluate the prevalence of security and privacy practices on a representative
sample of the Web, researchers rely on website popularity rankings such as the Alexa list …

This book is a comprehensive introduction to quantitative approaches to complex adaptive
systems. Practically all areas of life on this planet are constantly confronted with complex …

We present the largest and most detailed measurement of online tracking conducted to date,
based on a crawl of the top 1 million websites. We make 15 types of measurements on each …

This paper presents a state-of-the-art model for visual question answering (VQA), which won
the first place in the 2017 VQA Challenge. VQA is a task of significant importance for …

Multi-tenancy in modern datacenters is currently limited to a single latency-critical,
interactive service, running alongside one or more low-priority, best-effort jobs. This limits …

Attributed network embedding aims to seek low-dimensional vector representations for
nodes in a network, such that original network topological structure and node attribute …

Federated learning (FL) is a distributed deep learning method which enables multiple
participants, such as mobile phones and IoT devices, to contribute a neural network model …