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Full-Text Articles in Physical Sciences and Mathematics
Binary Classifiers For Noisy Datasets: A Comparative Study Of Existing Quantum Machine Learning Frameworks And Some New Approaches, Nikolaos Schetakis, Davit Aghamalyan, Paul Robert Griffin, Michael Boguslavsky
Binary Classifiers For Noisy Datasets: A Comparative Study Of Existing Quantum Machine Learning Frameworks And Some New Approaches, Nikolaos Schetakis, Davit Aghamalyan, Paul Robert Griffin, Michael Boguslavsky
Research Collection School Of Computing and Information Systems
This technology offer is a quantum machine learning algorithm applied to binary classification models for noisy datasets which are prevalent in financial and other datasets. By combining hybrid-neural networks, quantum parametric circuits, and data re-uploading we have improved the classification of non-convex 2-dimensional figures by understanding learning stability as noise increases in the dataset. The metric we use for assessing the performance of our quantum classifiers is the area under the receiver operator curve (ROC AUC). We are interested to collaborate with partners with use cases for binary classification of noisy data. Also, as quantum technology is still insufficient for …
Umaine Artificial Intelligence Webinar: Ai For Space And Aerospace Promotional Flyer, University Of Maine Artificial Intelligence, Institute Of Electrical And Electronics Engineers Maine Com/Cs Chapter, Vice President For Research And Dean Of The Graduate School
Umaine Artificial Intelligence Webinar: Ai For Space And Aerospace Promotional Flyer, University Of Maine Artificial Intelligence, Institute Of Electrical And Electronics Engineers Maine Com/Cs Chapter, Vice President For Research And Dean Of The Graduate School
General University of Maine Publications
Promotional flyer for the first webinar in the UMaine Artificial Intelligence 2021-2022 webinar series.
The University of Maine Artificial Intelligence Initiative (UMaine AI) is a unique Maine-based venture that brings together university, industry, government, and community collaborators from Maine and beyond to advance the field of artificial intelligence, and through development of innovative technologies and applications find transformative solutions to enhance human life and societal well-being in Maine and beyond.
Application Of Artificial Intelligence And Machine Learning In Libraries: A Systematic Review, Rajesh Kumar Das, Mohammad Sharif Ul Islam
Application Of Artificial Intelligence And Machine Learning In Libraries: A Systematic Review, Rajesh Kumar Das, Mohammad Sharif Ul Islam
Library Philosophy and Practice (e-journal)
As the concept and implementation of cutting-edge technologies like artificial intelligence and machine learning has become relevant, academics, researchers and information professionals involve research in this area. The objective of this systematic literature review is to provide a synthesis of empirical studies exploring application of artificial intelligence and machine learning in libraries. To achieve the objectives of the study, a systematic literature review was conducted based on the original guidelines proposed by Kitchenham et al. (2009). Data was collected from Web of Science, Scopus, LISA and LISTA databases. Following the rigorous/ established selection process, a total of thirty-two articles were …
Interpretability Of Ai In Computer Systems And Public Policy, Farzana Beente Yusuf
Interpretability Of Ai In Computer Systems And Public Policy, Farzana Beente Yusuf
FIU Electronic Theses and Dissertations
Advances in Artificial Intelligence (AI) have led to spectacular innovations and sophisticated systems for tasks that were thought to be capable only by humans. Examples include playing chess and Go, face and voice recognition, driving vehicles, and more. In recent years, the impact of AI has moved beyond offering mere predictive models into building interpretable models that appeal to human logic and intuition because they ensure transparency and simplicity and can be used to make meaningful decisions in real-world applications. A second trend in AI is characterized by important advancements in the realm of causal reasoning. Identifying causal relationships is …
Datascope: Predictive Diagnosis In Iiot-Enabled Smart Manufacturing, Adam Geltz, Reilly Sollenberger, Peilong Li
Datascope: Predictive Diagnosis In Iiot-Enabled Smart Manufacturing, Adam Geltz, Reilly Sollenberger, Peilong Li
Summer Scholarship, Creative Arts and Research Projects (SCARP)
This a collaborative project between Elizabethtown College and CPNet, LLC that is looking to help apply predictive modeling with CPNet’s domain knowledge to one of CPNet’s clients' IIoT manufacturing problems. CPNet has provided us with datasets taken from one of their clients in the hope that we can build a model that will be able to predict when a part within the machines they are looking at will fail and subsequently shut the machine down. We are trying to take their data and turn it into information that the company can take preemptive action on and save them downtime during …
Law Library Blog (January 2021): Legal Beagle's Blog Archive, Roger Williams University School Of Law
Law Library Blog (January 2021): Legal Beagle's Blog Archive, Roger Williams University School Of Law
Law Library Newsletters/Blog
No abstract provided.
Interpretable, Not Black-Box, Artificial Intelligence Should Be Used For Embryo Selection, Michael Anis Mihdi Afnan, Yanhe Liu, Vincent Conitzer, Cynthia Rudin, Abhishek Mishra, Julian Savulescu, Masoud Afnan
Interpretable, Not Black-Box, Artificial Intelligence Should Be Used For Embryo Selection, Michael Anis Mihdi Afnan, Yanhe Liu, Vincent Conitzer, Cynthia Rudin, Abhishek Mishra, Julian Savulescu, Masoud Afnan
Research outputs 2014 to 2021
Artificial intelligence (AI) techniques are starting to be used in IVF, in particular for selecting which embryos to transfer to the woman. AI has the potential to process complex data sets, to be better at identifying subtle but important patterns, and to be more objective than humans when evaluating embryos. However, a current review of the literature shows much work is still needed before AI can be ethically implemented for this purpose. No randomized controlled trials (RCTs) have been published, and the efficacy studies which exist demonstrate that algorithms can broadly differentiate well between ‘good-’ and ‘poor-’ quality embryos but …
Administrative Law In The Automated State, Cary Coglianese
Administrative Law In The Automated State, Cary Coglianese
All Faculty Scholarship
In the future, administrative agencies will rely increasingly on digital automation powered by machine learning algorithms. Can U.S. administrative law accommodate such a future? Not only might a highly automated state readily meet longstanding administrative law principles, but the responsible use of machine learning algorithms might perform even better than the status quo in terms of fulfilling administrative law’s core values of expert decision-making and democratic accountability. Algorithmic governance clearly promises more accurate, data-driven decisions. Moreover, due to their mathematical properties, algorithms might well prove to be more faithful agents of democratic institutions. Yet even if an automated state were …
Technology And The (Re)Construction Of Law, Christian Sundquist
Technology And The (Re)Construction Of Law, Christian Sundquist
Articles
Innovative advancements in technology and artificial intelligence have created a unique opportunity to re-envision both legal education and the practice of law. The COVID-19 pandemic has accelerated the technological disruption of both legal education and practice, as remote work, “Zoom” client meetings, virtual teaching, and online dispute resolution have become increasingly normalized. This essay explores how technological innovations in the coronavirus era are facilitating radical changes to our traditional adversarial system, the practice of law, and the very meaning of “legal knowledge.” It concludes with suggestions on how to reform legal education to better prepare our students for the emerging …