A Comprehensive Survey
By Yuxiang Ma, Yulei Wu, Jingguo Ge. Accountability and Privacy in Network Security, 2020
508 citations recorded by the source corpus.
Subfields: Computer Networks and Communications
View Paper: https://www.semanticscholar.org/paper/9f8b6e9ddd4e337c20a61789342e3b1a42c76ce0
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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
Citations in the corpus
- Artificial Intelligence for Mental Healthcare: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom (2021, background): “One potential solution to address small samples is transfer learning, which enables use of pretrained AI algorithms, designed for different purposes, as a starting point for analysis of new data (32).”
- A practical guide to multi-objective reinforcement learning and planning (2021, background): “The field of multi-objective evolutionary optimisation is already very well established [7, 30, 44, 169], and several researchers have applied concepts from this area to MORL tasks.”
- Attention, please! A survey of neural attention models in deep learning (2021, background): “GATs are an end-to-end attention version of GNNs (Wu et al.”
- A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker) (2021, methodology): “(1) A main repository (NAT_TOTAL for all countries and STATE_TOTAL for Brazil, the United States, the United Kingdom and Canada (2) A US repository (NAT_GOV and STATE_WIDE) (3) A Brazil repository (NAT_TOTAL, NAT_GOV, STATE_WIDE, STATE_GOV, CITY_TOTAL and CITY_WIDE)”
- DiffusionNet: Discretization Agnostic Learning on Surfaces (2020, methodology): “As a result, despite significant recent progress in geometric deep learning [Cao et al. 2020; Greengard 2020], current methods typically struggle to cope with the variability, complexity and scale encountered in the real-world surface and mesh-based settings.”