Academic Articles & Research Papers

Actors: A Model of Concurrent Computation in Distributed Systems

A foundational model of concurrency is developed in this thesis. It examines issues in the design of parallel systems and show why the actor model is suitable for exploiting large-scale parallelism. Concurrency in actors is constrained only...

Cybersecurity in Health Care

Abstract Ethical questions have always been crucial in health care; the rapid dissemination of ICT makes some of those questions even more pressing and also raises new ones. One of these new questions is cybersecurity in relation to ethics ...

Global Cybersecurity: New Directions in Theory and Methods

This thematic issue advocates a range of novel theoretical and methodological directions applicable to cybersecurity studies. Drawing on critical International Relations theory, Science and Technology Studies, participant observation, quant...

Cybersecurity

The internet has revolutionized the way people communicate, how they manage their business, and even how they conduct their studies. Organizations can conduct meetings virtually and store all their data online. With this convenience, howeve...

Crowdsourcing Cybersecurity

Social media is often viewed as a sensor into various societal events such as disease outbreaks, protests, and elections. We describe the use of social media as a crowdsourced sensor to gain insight into ongoing cyber-attacks. Our approach ...

Knowledge in the grey zone: AI and cybersecurity

Abstract Cybersecurity protects citizens and society from harm perpetrated through computer networks. Its task is made ever more complex by the diversity of actors—criminals, spies, militaries, hacktivists, firms—operating in global informa...

Semi-State Actors in Cybersecurity

Abstract What does the global telecommunications company Huawei, a hacking-for-hire outfit in India, and Russian cyber criminals have in common? They all share a special relationship to the state, which significantly shapes the politics of ...

Computer Vision and Natural Language Processing

Integrating computer vision and natural language processing is a novel interdisciplinary field that has received a lot of attention recently. In this survey, we provide a comprehensive introduction of the integration of computer vision and ...

Lexicography and natural language processing

The chapter introduces links between lexicography and natural language processing in both directions. First, how the lexicographic work benefits from techniques of natural language processing such as word sense disambiguation, semantic simi...

Neural Network Methods for Natural Language Processing

Deep learning has attracted dramatic attention in recent years, both in academia and industry. The popular term deep learning generally refers to neural network methods. Indeed, many core ideas and methods were born years ago in the era of ...

Representation Learning for Natural Language Processing

This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for NLP. It also benefit related domains such as machine learning, social network analysis, semantic Web, infor...

Natural Language Processing

In the modern age of information and analytics, natural language processing (NLP) is one of the most important technologies out there. Making sense of complex structures in language and deriving insights and actions from it are crucial from...

New trends in natural language processing: statistical natural language processing.

The field of natural language processing (NLP) has seen a dramatic shift in both research direction and methodology in the past several years. In the past, most work in computational linguistics tended to focus on purely symbolic methods. R...

Natural Language Processing

B eyond pattern recognition of individual alphanumeric characters , whether they be of fixed font or handwritten, lies the problem of understanding strings of characters that form words, sentences, or larger assemblages of text in a “natura...

A survey of uncertainty in deep neural networks

Abstract Over the last decade, neural networks have reached almost every field of science and become a crucial part of various real world applications. Due to the increasing spread, confidence in neural network predictions has become more a...

Statistical Mechanics of Neural Networks

A neural network is a large, highly interconnected assembly of simple elements. The elements, called neurons, are usually two-state devices that switch from one state to the other when their input exceeds a specific threshold value. In this...

A renaissance of neural networks in drug discovery

INTRODUCTION: Neural networks are becoming a very popular method for solving machine learning and artificial intelligence problems. The variety of neural network types and their application to drug discovery requires expert knowledge to cho...

Pointwise Convolutional Neural Networks

Deep learning with 3D data such as reconstructed point clouds and CAD models has received great research interests recently. However, the capability of using point clouds with convolutional neural network has been so far not fully explored....

Ensemble with neural networks for bankruptcy prediction

Neural Networks for Postprocessing Ensemble Weather Forecasts

Abstract Ensemble weather predictions require statistical postprocessing of systematic errors to obtain reliable and accurate probabilistic forecasts. Traditionally, this is accomplished with distributional regression models in which the pa...