Issue #192
February 26, 2023
- 1. The Importance of Probability in Data Science [kdnuggets.com]
- 2. AI won't make artists redundant - thanks to information theory [p.migdal.pl]
- 3. Researchers Discover a More Flexible Approach to Machine Learning [nautil.us]
- 4. Probability 101, the intuition behind martingales and solving problems with them [codeforces.com]
- 5. Model Selection with Imbalance Data: Only AUC may Not Save you [towardsdatascience.com]
- 6. A Quick Guide to Design Rigorous Machine Learning Experiments [towardsdatascience.com]
- 7. Getting to decisions faster in A/B tests – part 1: literature review [aurimas.eu]
- • Early morning university classes are associated with impaired sleep and academic performance (S. C. Yeo, C. K. Y. Lai, J. Tan, S. Lim, Y. Chandramoghan, T. K. Tan, J. J. Gooley)
- • Fundamental limits to learning closed-form mathematical models from data (O. Fajardo-Fontiveros, I. Reichardt, H. R. De Los Ríos, J. Duch, M. Sales-Pardo, R. Guimerà)
- • Influential nodes identification in complex networks: a comprehensive literature review (K. A. Rai, M. Machkour, J. Antari)
- • More Data Types More Problems: A Temporal Analysis of Complexity, Stability, and Sensitivity in Privacy Policies (J. Lovato, P. Mueller, P. Suchdev, P. S. Dodds)
- • Symbolic Discovery of Optimization Algorithms (X. Chen, C. Liang, D. Huang, E. Real, K. Wang, Y. Liu, H. Pham, X. Dong, T. Luong, C.-J. Hsieh, Y. Lu, Q. V. Le)
- • Epidemic control in networks with cliques: a mixed-order phase transition (L. D. Valdez, L. Vassallo, L. A. Braunstein)
- • Predicting Gender and Political Affiliation Using Mobile Payment Data (B. Stobaugh, D. Murthy)
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