Issue #47
April 19, 2020
- 1. Forecasting s-curves is hard [constancecrozier.com]
- 2. Event-Reduce - An algorithm to optimize database queries that run multiple times [github.com/pubkey]
- 3. The Hungarian Statistician Behind Three Volumes of Visualization Masterpieces [medium.com/nightingale]
- 4. Interpretability [fastforwardlabs.com]
- 5. How to know if artificial intelligence is about to destroy civilization [technologyreview.com]
- 6. Building a Social Network from the News using Graph Theory [towardsdatascience.com]
- 7. Monitoring Machine Learning Models in Production [christophergs.com]
- • Social-media companies must flatten the curve of misinformation (J. Donovan)
- • The Diversity–Innovation Paradox in Science (B. Hofstra, V. V. Kulkarni, S. M.-N. Galvez, B. He, D. Jurafsky, D. A. McFarland)
- • Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims (M. Brundage, S. Avin, J. Wang, H. Belfield, G. Krueger, et al)
- • Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies (M. Nagendran, Y. Chen, C. A. Lovejoy, A. C. Gordon, M. Komorowski, H. Harvey, E. J. Topol, J. P. A. Ioannidis, G. S. Collins)
- • Shortcut Learning in Deep Neural Networks (R. Geirhos, J.-H. Jacobsen, C. Michaelis, R. Zemel, W. Brendel, M. Bethge, F. A. Wichmann)
- • Datasets for Data-Driven Reinforcement Learning (J. Fu, A. Kumar, O. Nachum, G. Tucker, S. Levine)
- • Oversampling for Imbalanced Time Series Data (T. Zhu, Y. Lin, Y. Liu)
- • An In-depth Walkthrough on Evolution of Neural Machine Translation (R. Jagtap, S. N. Dhage)
A Taste of GPU Compute
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