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User Response Prediction in Online Advertising arXiv.cs.GL Pub Date : 2021-01-07 Zhabiz Gharibshah; Xingquan Zhu
Online advertising, as the vast market, has gained significant attention in various platforms ranging from search engines, third-party websites, social media, and mobile apps. The prosperity of online campaigns is a challenge in online marketing and is usually evaluated by user response through different metrics, such as clicks on advertisement (ad) creatives, subscriptions to products, purchases of
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Analog Computation and Representation arXiv.cs.GL Pub Date : 2020-12-10 Corey J. Maley
Relative to digital computation, analog computation has been neglected in the philosophical literature. To the extent that attention has been paid to analog computation, it has been misunderstood. The received view -- that analog computation has to do essentially with continuity -- is simply wrong, as shown by careful attention to historical examples of discontinuous, discrete analog computers. Instead
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Deep Learning for Human Mobility: a Survey on Data and Models arXiv.cs.GL Pub Date : 2020-12-04 Massimiliano Luca; Gianni Barlacchi; Bruno Lepri; Luca Pappalardo
The study of human mobility is crucial due to its impact on several aspects of our society, such as disease spreading, urban planning, well-being, pollution, and more. The proliferation of digital mobility data, such as phone records, GPS traces, and social media posts, combined with the outstanding predictive power of artificial intelligence, triggered the application of deep learning to human mobility
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Resolving the cybersecurity Data Sharing Paradox to scale up cybersecurity via a co-production approach towards data sharing arXiv.cs.GL Pub Date : 2020-11-20 Amir Atapour-Abarghouei; Andrew Stephen McGough; David Stanley Wall
As cybercriminals scale up their operations to increase their profits or inflict greater harm, we argue that there is an equal need to respond to their threats by scaling up cybersecurity. To achieve this goal, we have to develop a co-productive approach towards data collection and sharing by overcoming the cybersecurity data sharing paradox. This is where we all agree on the definition of the problem
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Revising the classic computing paradigm and its technological implementations arXiv.cs.GL Pub Date : 2020-11-16 János Végh
Today's computing is told to be based on the classic paradigm, proposed by von Neumann, a three-quarter century ago. However, that paradigm was justified (for the timing relations of) vacuum tubes only. The technological development invalidated the classic paradigm (but not the model!) and led to catastrophic performance losses in computing systems, from operating gate level to large networks, including
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Hints and Principles for Computer System Design arXiv.cs.GL Pub Date : 2020-11-03 Butler Lampson
This new long version of my 1983 paper suggests the goals you might have for your system -- Simple, Timely, Efficient, Adaptable, Dependable, Yummy (STEADY) -- and techniques for achieving them -- Approximate, Incremental, Divide & Conquer (AID). It also gives some principles for system design that are more than just hints, and many examples of how to apply the ideas.
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Poster: A Real-World Distributed Infrastructure for Processing Financial Data at Scale arXiv.cs.GL Pub Date : 2020-10-29 Sebastian Frischbier; Mario Paic; Alexander Echler; Christian Roth
Financial markets are event- and data-driven to an extremely high degree. For making decisions and triggering actions stakeholders require notifications about significant events and reliable background information that meet their individual requirements in terms of timeliness, accuracy, and completeness. As one of Europe's leading providers of financial data and regulatory solutions vwd processes an
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Three computational models and its equivalence arXiv.cs.GL Pub Date : 2020-10-26 Ciro Ivan Garcia Lopez
The study of computability has its origin in Hilbert's conference of 1900, where an adjacent question, to the ones he asked, is to give a precise description of the notion of algorithm. In the search for a good definition arose three independent theories: Turing and the Turing machines, G\"odel and the recursive functions, Church and the Lambda Calculus. Later there were established by Kleene that
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Smart Anomaly Detection in Sensor Systems arXiv.cs.GL Pub Date : 2020-10-27 L. Erhan; M. Ndubuaku; M. Di Mauro; W. Song; M. Chen; G. Fortino; O. Bagdasar; A. Liotta
Anomaly detection is concerned with identifying data patterns that deviate remarkably from the expected behaviour. This is an important research problem, due to its broad set of application domains, from data analysis to e-health, cybersecurity, predictive maintenance, fault prevention, and industrial automation. Herein, we review state-of-the-art methods that may be employed to detect anomalies in
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Achieving a quantum smart workforce arXiv.cs.GL Pub Date : 2020-10-23 Clarice D. Aiello; D. D. Awschalom; Hannes Bernien; Tina Brower-Thomas; Kenneth R. Brown; Todd A. Brun; Justin R. Caram; Eric Chitambar; Rosa Di Felice; Michael F. J. Fox; Stephan Haas; Alexander W. Holleitner; Eric R. Hudson; Jeffrey H. Hunt; Robert Joynt; Scott Koziol; H. J. Lewandowski; Douglas T. McClure; Jens Palsberg; Gina Passante; Kristen L. Pudenz; Christopher J. K. Richardson; Jessica L.
Interest in building dedicated Quantum Information Science and Engineering (QISE) education programs has greatly expanded in recent years. These programs are inherently convergent, complex, often resource intensive and likely require collaboration with a broad variety of stakeholders. In order to address this combination of challenges, we have captured ideas from many members in the community. This
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On licenses for [Open] Hardware arXiv.cs.GL Pub Date : 2020-10-18 Màrius Montón; Xavier Salazar
This document explains the basic concepts related to software and hardware licenses, and it summarizes the most popular licenses that are currently used for hardware projects. Two case studies of hardware projects at different levels of abstraction are also presented, together with a discussion of license applicability, commercial issues, code protection, and related concerns. This paper intends to
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ACM SIGSOFT Empirical Standards arXiv.cs.GL Pub Date : 2020-10-07 Paul Ralph; Sebastian Baltes; Domenico Bianculli; Yvonne Dittrich; Michael Felderer; Robert Feldt; Antonio Filieri; Carlo Alberto Furia; Daniel Graziotin; Pinjia He; Rashina Hoda; Natalia Juristo; Barbara Kitchenham; Romain Robbes; Daniel Mendez; Jefferson Molleri; Diomidis Spinellis; Miroslaw Staron; Klaas Stol; Damian Tamburri; Marco Torchiano; Christoph Treude; Burak Turhan; Sira Vegas
Empirical Standards are brief public document that communicate expectations for a specific kind of study (e.g. a questionnaire survey). The ACM SIGSOFT Paper and Peer Review Quality Initiative generated empirical standards for common research methods in software engineering. These living documents, which should be continuously revised to reflect evolving consensus around research best practices, can
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Edsger Dijkstra. The Man Who Carried Computer Science on His Shoulders arXiv.cs.GL Pub Date : 2020-10-01 Krzysztof R. Apt
This a biographical essay about Edsger Wybe Dijkstra.
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A Survey on Semantic Parsing from the perspective of Compositionality arXiv.cs.GL Pub Date : 2020-09-29 Pawan Kumar; Srikanta Bedathur
Different from previous surveys in semantic parsing (Kamath and Das, 2018) and knowledge base question answering(KBQA)(Chakraborty et al., 2019; Zhu et al., 2019; Hoffner et al., 2017) we try to takes a different perspective on the study of semantic parsing. Specifically, we will focus on (a)meaning composition from syntactical structure(Partee, 1975), and (b) the ability of semantic parsers to handle
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Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases arXiv.cs.GL Pub Date : 2020-09-24 Gerhard Weikum; Luna Dong; Simon Razniewski; Fabian Suchanek
Equipping machines with comprehensive knowledge of the world's entities and their relationships has been a long-standing goal of AI. Over the last decade, large-scale knowledge bases, also known as knowledge graphs, have been automatically constructed from web contents and text sources, and have become a key asset for search engines. This machine knowledge can be harnessed to semantically interpret
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From the digital data revolution to digital health and digital economy toward a digital society: Pervasiveness of Artificial Intelligence arXiv.cs.GL Pub Date : 2020-08-03 Frank Emmert-Streib
Technological progress has led to powerful computers and communication technologies that penetrate nowadays all areas of science, industry and our private lives. As a consequence, all these areas are generating digital traces of data amounting to big data resources. This opens unprecedented opportunities but also challenges toward the analysis, management, interpretation and utilization of these data
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Sulla decifratura di Enigma -- Come un reverendo del XVIII secolo contribuì alla sconfitta degli U-boot tedeschi durante la Seconda Guerra Mondiale arXiv.cs.GL Pub Date : 2020-07-17 Fabio S. Priuli; Claudia Violante
This article, written in Italian language, explores the contribution given by Bayes' rule and by subjective probability in the work at Bletchley Park towards cracking Enigma cyphered messages during WWII. -- In questo articolo, scritto in Italiano, esploriamo il contributo dato dal teorema di Bayes e dalle idee della probabilit\`a soggettiva nel lavoro compiuto a Bletchley Park che ha portato a decifrare
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MiniConf -- A Virtual Conference Framework arXiv.cs.GL Pub Date : 2020-07-10 Alexander M. Rush; Hendrik Strobelt
MiniConf is a framework for hosting virtual academic conferences motivated by the sudden inability for these events to be hosted globally. The framework is designed to be global and asynchronous, interactive, and to promote browsing and discovery. We developed the system to be sustainable and maintainable, in particular ensuring that it is open-source, easy to setup, and scalable on minimal hardware
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Kolmogorov's legacy: Algorithmic Theory of Informatics and Kolmogorov Programmable Technology arXiv.cs.GL Pub Date : 2020-06-21 Sergei LevashkinArtificial Intelligence Lab, Moscow. Russia; Victor AlexandrovRussian Academy of Sciences, Saint Petersburg, Russia; Adolfo Guzmán-ArenasInstituto Politécnico Nacional, Mexico City, Mexico
In this survey, we explore Andrei Nikolayevich Kolmogorov's seminal work in just one of his many facets: its influence Computer Science especially his viewpoint of what herein we call 'Algorithmic Theory of Informatics.' Can a computer file 'reduce' its 'size' if we add to it new symbols? Do equations of state like second Newton law in Physics exist in Computer Science? Can Leibniz' principle of identification
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Value-based Engineering for Ethics by Design arXiv.cs.GL Pub Date : 2020-04-28 Sarah Spiekermann; Till Winkler
This article gives a methodological overview of Value-based Engineering for ethics by design. It discusses key challenges and measures involved in eliciting, conceptualizing, prioritizing and respecting values in system design. Thereby it draws from software engineering, value sensitive design, design thinking and participatory design as well as from philosophical sources, especially Material Ethics
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An Environment for Sustainable Research Software in Germany and Beyond: Current State, Open Challenges, and Call for Action arXiv.cs.GL Pub Date : 2020-04-27 Hartwig Anzt; Felix Bach; Stephan Druskat; Frank Löffler; Axel Loewe; Bernhard Y. Renard; Gunnar Seemann; Alexander Struck; Elke Achhammer; Piush Aggarwal; Franziska Appel; Michael Bader; Lutz Brusch; Christian Busse; Gerasimos Chourdakis; Piotr W. Dabrowski; Peter Ebert; Bernd Flemisch; Sven Friedl; Bernadette Fritzsch; Maximilian D. Funk; Volker Gast; Florian Goth; Jean-Noël Grad; Sibylle Hermann;
Research software has become a central asset in academic research. It optimizes existing and enables new research methods, implements and embeds research knowledge, and constitutes an essential research product in itself. Research software must be sustainable in order to understand, replicate, reproduce, and build upon existing research or conduct new research effectively. In other words, software
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On the Evaluation of Military Simulations: Towards A Taxonomy of Assessment Criteria arXiv.cs.GL Pub Date : 2020-04-20 Mario Golling; Robert Koch; Peter Hillmann; Volker Eiseler; Lars Stiemert; Andres Rekker
In the area of military simulations, a multitude of different approaches is available. Close Combat Tactical Trainer, Joint Tactical Combat Training System, Battle Force Tactical Training or Warfighter's Simulation 2000 are just some examples within the history of the large DoD Development Program in Modelling and Simulation, representing just a small piece of the variety of diverse solutions. Very
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Human Factors in Biocybersecurity Wargames arXiv.cs.GL Pub Date : 2020-04-18 Lucas Potter; Xavier-Lewis Palmer
Within the field of biocybersecurity, it is important to understand what vulnerabilities may be uncovered in the processing of biologics as well as how they can be safeguarded as they intersect with cyber and cyberphysical systems, as noted by the Peccoud Lab, to ensure not only product and brand integrity, but protect those served. Recent findings have revealed that biological systems can be used
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From Horseback Riding to Changing the World: UX Competence as a Journey arXiv.cs.GL Pub Date : 2020-04-16 Omar Sosa-Tzec; Erik Stolterman Bergqvist; Marty A. Siegel
In this paper, we explore the notion of competence in UX based on the perspective of practitioners. As a result of this exploration, we observed four domains through which we conceptualize a plan of sources of competence that describes the ways a UX practitioner develop competence. Based on this plane, we present the idea of competence as a journey. A journey whose furthest stage implies an urge towards
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Knowledge Scientists: Unlocking the data-driven organization arXiv.cs.GL Pub Date : 2020-04-16 George Fletcher; Paul Groth; Juan Sequeda
Organizations across all sectors are increasingly undergoing deep transformation and restructuring towards data-driven operations. The central role of data highlights the need for reliable and clean data. Unreliable, erroneous, and incomplete data lead to critical bottlenecks in processing pipelines and, ultimately, service failures, which are disastrous for the competitive performance of the organization
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Foundations of Explainable Knowledge-Enabled Systems arXiv.cs.GL Pub Date : 2020-03-17 Shruthi Chari; Daniel M. Gruen; Oshani Seneviratne; Deborah L. McGuinness
Explainability has been an important goal since the early days of Artificial Intelligence. Several approaches for producing explanations have been developed. However, many of these approaches were tightly coupled with the capabilities of the artificial intelligence systems at the time. With the proliferation of AI-enabled systems in sometimes critical settings, there is a need for them to be explainable
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The Data Science Fire Next Time: Innovative strategies for mentoring in data science arXiv.cs.GL Pub Date : 2020-03-01 Latifa Jackson; Heriberto Acosta Maestre
As data mining research and applications continue to expand in to a variety of fields such as medicine, finance, security, etc., the need for talented and diverse individuals is clearly felt. This is particularly the case as Big Data initiatives have taken off in the federal, private and academic sectors, providing a wealth of opportunities, nationally and internationally. The Broadening Participation
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Artificial Intelligence, Chaos, Prediction and Understanding in Science arXiv.cs.GL Pub Date : 2020-03-03 Miguel A. F. Sanjuán
Machine learning and deep learning techniques are contributing much to the advancement of science. Their powerful predictive capabilities appear in numerous disciplines, including chaotic dynamics, but they miss understanding. The main thesis here is that prediction and understanding are two very different and important ideas that should guide us about the progress of science. Furthermore, it is emphasized
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Gender Disparities in International Research Collaboration: A Large-scale Bibliometric Study of 25,000 University Professors arXiv.cs.GL Pub Date : 2020-03-01 Marek Kwiek; Wojciech Roszka
In this research, we examine the hypothesis that gender disparities in international research collaboration differ by collaboration intensity, academic position, age, and academic discipline. The following are the major findings: (1) while female scientists exhibit a higher rate of general, national, and institutional collaboration, male scientists exhibit a higher rate of international collaboration
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How to democratize Internet of Things devices. A participatory design study to improve digital literacy arXiv.cs.GL Pub Date : 2020-02-15 Matteo Zallio; John McGrory; Damon Berry
The global introduction of affordable Internet of Things (IoT) devices offers an opportunity to empower a large variety of users with different needs. However, many off-the-shelf digital products are still not widely adopted by people who are hesitant technology users or by older adults, notwithstanding that the design and user-interaction of these devices is recognized to be user-friendly. In view
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The need for modern computing paradigm: Science applied to computing arXiv.cs.GL Pub Date : 2019-08-02 János Végh
More than hundred years ago the 'classic physics' was it in its full power, with just a few unexplained phenomena; which however led to a revolution and the development of the 'modern physics'. Today the computing is in a similar position: computing is a sound success story, with exponentially growing utilization, but with a growing number of difficulties and unexpected issues as moving towards extreme
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