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pro vyhledávání: '"Verma, Dinesh P"'
Quantum Communications Networks using the properties of qubits, namely state superposition, no-cloning and entanglement, can enable the exchange of information in a very secure manner across optical links or free space. New innovations enable the use
Externí odkaz:
http://arxiv.org/abs/2305.20013
Autor:
Dunbar, Daniel, Hagedorn, Thomas, Blackburn, Mark, Dzielski, John, Hespelt, Steven, Kruse, Benjamin, Verma, Dinesh, Yu, Zhongyuan
Engineered solutions are becoming more complex and multi-disciplinary in nature. This evolution requires new techniques to enhance design and analysis tasks that incorporate data integration and interoperability across various engineering tool suites
Externí odkaz:
http://arxiv.org/abs/2206.10454
Increased adoption of artificial intelligence (AI) systems into scientific workflows will result in an increasing technical debt as the distance between the data scientists and engineers who develop AI system components and scientists, researchers an
Externí odkaz:
http://arxiv.org/abs/2103.03610
Autor:
Jabal, Amani Abu, Bertino, Elisa, Lobo, Jorge, Verma, Dinesh, Calo, Seraphin, Russo, Alessandra
Technology advances in areas such as sensors, IoT, and robotics, enable new collaborative applications (e.g., autonomous devices). A primary requirement for such collaborations is to have a secure system which enables information sharing and informat
Externí odkaz:
http://arxiv.org/abs/2010.09767
Akademický článek
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Increased adoption and deployment of machine learning (ML) models into business, healthcare and other organisational processes, will result in a growing disconnect between the engineers and researchers who developed the models and the model's users a
Externí odkaz:
http://arxiv.org/abs/1907.03483
Researchers and scientists use aggregations of data from a diverse combination of sources, including partners, open data providers and commercial data suppliers. As the complexity of such data ecosystems increases, and in turn leads to the generation
Externí odkaz:
http://arxiv.org/abs/1904.04253
Machine Learning systems rely on data for training, input and ongoing feedback and validation. Data in the field can come from varied sources, often anonymous or unknown to the ultimate users of the data. Whenever data is sourced and used, its consum
Externí odkaz:
http://arxiv.org/abs/1904.03045
Akademický článek
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The different sets of regulations existing for differ-ent agencies within the government make the task of creating AI enabled solutions in government dif-ficult. Regulatory restrictions inhibit sharing of da-ta across different agencies, which could
Externí odkaz:
http://arxiv.org/abs/1809.10036