NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature

18 December 2018

Papers citing "NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature"

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Stratified cross-validation for unbiased and privacy-preserving federated learning R. Bey Romain Goussault M. Benchoufi R. Porcher FedML 208 12 0 22 Jan 2020
ModelHub.AI: Dissemination Platform for Deep Learning Models A. Hosny M. Schwier Christoph Berger Evin Pınar Örnek Mehmet Turan ... U. Hoffmann Bjoern Menze Spyridon Bakas Andrey Fedorov Hugo J. W. L. Aerts VLM 109 19 0 26 Nov 2019
Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness Sebastian J. Vollmer Bilal A. Mateen G. Bohner Franz J. Király Rayid Ghani ... Karel G. M. Moons Gary S. Collins J. Ioannidis Chris Holmes H. Hemingway 168 39 0 21 Dec 2018