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Safe Use of AI: Hear from AvePoint Co-Founder & CEO with Former Congressman from #shifthappens in DC

Tech Edge hosted a fireside chat with Co-Founder & CEO Dr. Tianyi Jiang (TJ) of AvePoint (Nasdaq: AVPT) with Former U.S. Congressman Jerry McNerney at the #shifthappens Conference in Washington, D.C. The in-person interview was joined by Editor-at-Large Jarrett Banks and they discussed a range of topics including safe and effective use of AI technology across industries, better […]
United States New Jersey Jerry Mcnerney Gerald Mcnerney Commerce Committee Information Technology Products Or Services
Source: yahoo.com

AI in Data Security – Hear from AvePoint CEO TJ Jiang, Live from #Shifthappens Conference in Washington, D.C.

Tech Edge hosted a fireside chat with Dr. Tianyi Jiang (TJ), CEO and Co-Founder of AvePoint (Nasdaq: AVPT), live at the #Shifthappens Conference in Washington, D.C. The in-person interview was joined by Editor-at-Large Jarrett Banks and they discussed a range of topics including the use of AI in data security, the newly-launched Avepoint Opus and much […]
United States New Jersey Information Technology Products Or Services Department Of Information Systems Ernst Young Stern School Of Business
Source: yahoo.com

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Adversarial competition and collusion in algorithmic markets | Nature Machine Intelligence

Algorithms are now playing a central role in digital marketplaces, setting prices and automatically responding in real time to competitors’ behaviour. The deployment of automated pricing algorithms is scrutinized by economists and regulatory agencies, concerned about its impact on prices and competition. Existing research has so far been limited to cases where all firms use the same algorithm, suggesting that anti-competitive behaviour might spontaneously arise in that setting. Here we int...
United Kingdom Great Britain Michael Eisen Bruno Salcedo Office For National Statistics International World Wide Web Conferences Steering Committee
Source: nature.com

"Predicting lung cancer survival based on clinical data using machine l" by Fatimah Abdulazim Altuhaifa, Khin Than Win et al.

Machine learning has gained popularity in predicting survival time in the medical field. This review examines studies utilizing machine learning and data-mining techniques to predict lung cancer survival using clinical data. A systematic literature review searched MEDLINE, Scopus, and Google Scholar databases, following reporting guidelines and using the COVIDENCE system. Studies published from 2000 to 2023 employing machine learning for lung cancer survival prediction were included. Risk of bia...
Google Scholar Artificial Intelligence Data Mining Feature Selection Lung Cancer Machine Learning
Source: uow.edu.au

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