Zobrazeno 1 - 10 of 212 pro vyhledávání: '"Algorithmic inference"'
1
6GAN: IPv6 Multi-Pattern Target Generation via Generative Adversarial Nets with Reinforcement Learning
Autor: Tianyu Cui, Gaopeng Gou, Peipei Fu, Gang Xiong, Zhen Li, Chang Liu
Publikováno v: INFOCOM
Global IPv6 scanning has always been a challenge for researchers because of the limited network speed and computational power. Target generation algorithms are recently proposed to overcome the problem for Internet assessments by predicting a candida
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d4e4542cf17fee877ed882276ef16ba0
http://arxiv.org/abs/2204.09839
Zobrazit plný text záznamu
3
Algorithmic inference, political interest, and exposure to news and politics on Facebook
Autor: Mel Medeiros, Kelley Cotter, Kjerstin Thorson, Chankyung Pak
Publikováno v: Information, Communication & Society. 24:183-200
The visibility of news and politics in a Facebook newsfeed depends on the actions of a diverse set of actors: users, their friends, content publishers such as news organizations, advertisers, and a...
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f388902de52fb42f2151c6ae01f81a09
https://doi.org/10.1080/1369118x.2019.1642934
Zobrazit plný text záznamu
6
Comparing Inference Methods for Non-probability Samples
Publikováno v: International Statistical Review. 86(2):322-343
Social and economic scientists are tempted to use emerging data sources like big data to compile information about finite populations as an alternative for traditional survey samples. These data sources generally cover an unknown part of the populati
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dris___00893::fd9146a091a9583612448cc231cafa44
https://doi.org/10.1111/insr.12253
Zobrazit plný text záznamu
7
Comparing Inference Methods for Non-probability Samples
Autor: Jan van den Brakel, Bart Buelens, Joep Burger
Publikováno v: International Statistical Review. 86:322-343
Social and economic scientists are tempted to use emerging data sources like big data to compile information about finite populations as an alternative for traditional survey samples. These data sources generally cover an unknown part of the populati
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2a8b320a93577c87b462d923037abef5
https://doi.org/10.1111/insr.12253
Zobrazit plný text záznamu
9
On some statistical models with a random number of observations
Autor: João T. Mexia, Pedro P. Mota, Manuel L. Esquível
Publikováno v: Journal of Statistical Theory and Practice. 10:805-823
We extend some classical statistical inference to the case of a random number of observations with a stabilized distribution: namely, in the normal model, inference for the mean with known and unknown variance and inference for the variance. We descr
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::412275398c608ad7f718be96b6379d3b
https://doi.org/10.1080/15598608.2016.1227735
Zobrazit plný text záznamu
10
Magnitude-based inference and its application in user research
Autor: Matthew Weston, Paul van Schaik
Publikováno v: International Journal of Human-Computer Studies. 88:38-50
Magnitude-based inference offers a theoretically justified and practically useful approach in any behavioural research that involves statistical inference. This approach supports two important types of inference: mechanistic inference and practical i
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d81379407e754696e9bbf32daa728c40
https://doi.org/10.1016/j.ijhcs.2016.01.002
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje