Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Qin, Xiangju"'
Autor:
Aa, Tom Vander, Qin, Xiangju, Blomstedt, Paul, Wuyts, Roel, Verachtert, Wilfried, Kaski, Samuel
Matrix factorization is a very common machine learning technique in recommender systems. Bayesian Matrix Factorization (BMF) algorithms would be attractive because of their ability to quantify uncertainty in their predictions and avoid over-fitting,
Externí odkaz:
http://arxiv.org/abs/2004.02561
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Matrix completion aims to predict missing elements in a partially observed data matrix which in typical applications, such as collaborative filtering, is large and extremely sparsely observed. A standard solution is matrix factorization, which predic
Externí odkaz:
http://arxiv.org/abs/1908.01009
Publikováno v:
Machine Learning, 2019
Bayesian matrix factorization (BMF) is a powerful tool for producing low-rank representations of matrices and for predicting missing values and providing confidence intervals. Scaling up the posterior inference for massive-scale matrices is challengi
Externí odkaz:
http://arxiv.org/abs/1703.00734
Collaborations such as Wikipedia are a key part of the value of the modern Internet. At the same time there is concern that these collaborations are threatened by high levels of member turnover. In this paper we borrow ideas from topic analysis to ed
Externí odkaz:
http://arxiv.org/abs/1407.7736
One of the more disruptive reforms associated with the modern Internet is the emergence of online communities working together on knowledge artefacts such as Wikipedia and OpenStreetMap. Recently it has become clear that these initiatives are vulnera
Externí odkaz:
http://arxiv.org/abs/1401.7890
Autor:
Qin, Xiangju, Cunningham, Pádraig
Publikováno v:
The 23rd Irish Conference on Artificial Intelligence and Cognitive Science (AICS 2012), p.p. 3--11
In this paper we address the challenge of assessing the quality of Wikipedia pages using scores derived from edit contribution and contributor authoritativeness measures. The hypothesis is that pages with significant contributions from authoritative
Externí odkaz:
http://arxiv.org/abs/1206.2517
Autor:
Zhou, Pu, Liu, Mingxing, Yang, Kunshan, Dong, Weizhun, Shi, Fangfei, Du, Xiu, Qin, Xiangju, Zhong, Yu, Geng, Wentong, Kong, Lingxin
Publikováno v:
Proceedings of SPIE; March 2024, Vol. 13104 Issue: 1 p131041C-131041C-6, 1179376p
Publikováno v:
In Social Networks October 2015 43:1-15
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.