Issue #105
May 30, 2021
- 1. How To Count A Billion Distinct Objects Using Only 1.5KB Of Memory [highscalability.com]
- 2. Hacker's guide to deep-learning side-channel attacks: the theory [elie.net]
- 3. Here are the data brokers quietly buying and selling your personal information [fastcompany.com]
- 4. Potemkin Data Science [mcorrell.medium.com]
- 5. Datasets for Google Cloud: Introducing our new reference architecture [cloud.google.com]
- 6. Be Careful When Interpreting Predictive Models in Search of Causal Insights [towardsdatascience.com]
- 7. Advancing sports analytics through AI research [deepmind.com]
- 8. How to Build a Machine Learning App [towardsdatascience.com]
- • Impacts of social distancing policies on mobility and COVID-19 case growth in the US (G. A. Wellenius, S. Vispute, V. Espinosa, A. Fabrikant, T. C. Tsai, J. Hennessy, A. Dai, B. Williams, K. Gadepalli, A. Boulanger, A. Pearce, C. Kamath, et al)
- • The universal visitation law of human mobility (M. Schläpfer, L. Dong, K. O’Keeffe, P. Santi, M. Szell, H. Salat, S. Anklesaria, M. Vazifeh, C. Ratti, G. B. West)
- • Motifs for processes on networks (A. C. Schwarze, M. A. Porter)
- • Are Pre-trained Convolutions Better than Pre-trained Transformers? (Y. Tay, M. Dehghani, J. Gupta, D. Bahri, V. Aribandi, Z. Qin, D. Metzler)
- • Efficient hypothesis testing for community detection in heterogeneous networks by graph dissimilarity (X.-J. Xu, C. Chen, J. F. F. Mendes)
- • Balancing the Spread of Two Opinions in Sparse Social Networks (D. Knop, Š. Schierreich, O. Suchý)
- • Generalised learning of time-series: Ornstein-Uhlenbeck processes (M. Süzen, A. Yegenoglu)
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