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Showing 20 of 1,126 academic articles
Michael Paluszek, Stephanie J. Thomas • Apress eBooks
(2016)
This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It prov...
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DOI: https://doi.org/10.1007/978-1-4842-2250-8
Tim Mueller, Aaron Gilad Kusne, Rampi Ramprasad • Reviews in computational chemistry
(2016)
This chapter addresses the role that data-driven approaches, especially machine learning methods, are expected to play in materials research in the immediate future. Machine learning, an important part of artificial intelligence, has made m...
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DOI: https://doi.org/10.1002/9781119148739.ch4
Hilal M. El Misilmani, Tarek Naous • International Conference on High Performance Computing & Simulation (HPCS)
(2019)
With the growth and wide variety of available data, advanced processing, and affordable data storage, machine learning is witnessing great attention in finding optimized solutions in various fields. Machine learning techniques are currently...
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DOI: https://doi.org/10.1109/hpcs48598.2019.9188224
Ling Huang, Anthony D. Joseph, Blaine A. Nelson, Benjamin I. P. Rubinstein et al. • ACM Workshop on Artificial Intelligence and Security (AISec)
(2011)
In this paper (expanded from an invited talk at AISEC 2010), we discuss an emerging field of study: adversarial machine learning---the study of effective machine learning techniques against an adversarial opponent. In this paper, we: give a...
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DOI: https://doi.org/10.1145/2046684.2046692
Feiyun Cui, Yun Yue, Yi Zhang, Ziming Zhang et al. • ACS Sensors
(2020)
Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis. Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved impressive advances. However, novel advanced ML methods, es...
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DOI: https://doi.org/10.1021/acssensors.0c01424
Sebastian Raschka, Joshua M. Patterson, Corey Nolet • Information
(2020)
Smarter applications are making better use of the insights gleaned from data, having an impact on every industry and research discipline. At the core of this revolution lies the tools and the methods that are driving it, from processing the...
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DOI: https://doi.org/10.3390/info11040193
Sarah J. MacEachern, Nils D. Forkert • Genome
(2020)
Precision medicine is an emerging approach to clinical research and patient care that focuses on understanding and treating disease by integrating multi-modal or multi-omics data from an individual to make patient-tailored decisions. With t...
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Open Access
DOI: https://doi.org/10.1139/gen-2020-0131
Michael I. Jordan, Tom M. Mitchell • Science
(2015)
Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today's most rapidly growing technical fields, lying at the intersection of computer science and statistics, and a...
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DOI: https://doi.org/10.1126/science.aaa8415
JUDE W. SHAVLIK, Thomas E. Deitterich, Thomas G. Dietterich (1991)
From the Publisher:
The ability to learn is a fundamental characteristic of intelligent behavior. Consequently, machine learning has been a focus of artificial intelligence since the beginnings of AI in the 1950s. The 1980s saw tremendous ...
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Bernhard Schölkopf • ACM eBooks
(2022)
Graphical causal inference as pioneered by Judea Pearl arose from research on artificial intelligence (AI), and for a long time had little connection to the field of machine learning. This article discusses where links have been and should ...
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Open Access
DOI: https://doi.org/10.1145/3501714.3501755
Solveig Badillo, Balázs Bánfai, Fabian Birzele, Iakov I. Davydov et al. • Clinical Pharmacology & Therapeutics
(2020)
In the last few years, machine learning (ML) and artificial intelligence have seen a new wave of publicity fueled by the huge and ever-increasing amount of data and computational power as well as the discovery of improved learning algorithm...
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cc-by-nc-nd
DOI: https://doi.org/10.1002/cpt.1796
PMC: 7189875
• Series in machine perception and artificial intelligence
(2019)
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict ...
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DOI: https://doi.org/10.1142/9789811201967_0001
Ethem Alpaydın • The MIT Press eBooks
(2021)
A concise overview of machine learning—computer programs that learn from data—the basis of such applications as voice recognition and driverless cars. Today, machine learning underlies a range of applications we use every day, from product ...
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Open Access
DOI: https://doi.org/10.7551/mitpress/13811.001.0001
Christian Janiesch, Patrick Zschech, Kai Heinrich • Electronic Markets
(2021)
Abstract Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of a...
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DOI: https://doi.org/10.1007/s12525-021-00475-2
Kareem Ayoub, Kenneth Payne • Journal of Strategic Studies
(2015)
We argue that Artificial Intelligence (AI) will, in the very near future, have a profound impact on the conduct of strategy and will be disruptive of existing power balances. To do so, we review the psychological foundations of strategy and...
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DOI: https://doi.org/10.1080/01402390.2015.1088838
Andrew Martin Cox, Suvodeep Mazumdar A • Journal of Librarianship and Information Science
(2022)
The aim of the paper is to define Artificial Intelligence (AI) for librarians by examining general definitions of AI, analysing the umbrella of technologies that make up AI, defining types of use case by area of library operation, and then ...
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DOI: https://doi.org/10.1177/09610006221142029
Erik J. Larson • Harvard University Press eBooks
(2021)
Futurists are certain that humanlike AI is on the horizon, but in fact engineers have no idea how to program human reasoning. AI reasons from statistical correlations across data sets, while common sense is based heavily on conjecture. Erik...
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DOI: https://doi.org/10.2307/j.ctv322v43j
Michael Gofman, Zhao Jin • The Journal of Finance
(2023)
ABSTRACT We document an unprecedented brain drain of Artificial Intelligence (AI) professors from universities from 2004 to 2018. We find that students from the affected universities establish fewer AI startups and raise less funding. The b...
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cc-by-nc-nd
DOI: https://doi.org/10.1111/jofi.13302
S. Pradeesh Hosea, V. Harikrishnan, K. Rajkumar • International Conference on Electronics Computer Technology
(2011)
Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on repres...
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DOI: https://doi.org/10.1109/icectech.2011.5941871
Chiara Longoni, Andrea Bonezzi, Carey K. Morewedge • Journal of Consumer Research
(2019)
Abstract Artificial intelligence (AI) is revolutionizing healthcare, but little is known about consumer receptivity to AI in medicine. Consumers are reluctant to utilize healthcare provided by AI in real and hypothetical choices, separate a...
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Open Access
DOI: https://doi.org/10.1093/jcr/ucz013