Zobrazeno 31 - 40
of 55
pro vyhledávání: '"JINFENG YI"'
Publikováno v:
ACL (1)
Visual language grounding is widely studied in modern neural image captioning systems, which typically adopts an encoder-decoder framework consisting of two principal components: a convolutional neural network (CNN) for image feature extraction and a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a67e5332f567e55c0805faf66c682f9
Publikováno v:
Machine Learning. 99:353-372
Distance metric learning (DML) is an important task that has found applications in many domains. The high computational cost of DML arises from the large number of variables to be determined and the constraint that a distance metric has to be a posit
Publikováno v:
IEEE BigData
Estimating the skills, talents, and expertise of employees is essential for human capital management in knowledge-based organizations across industries and sectors. In this paper, we describe an approach to infer the expertise of employees from their
Publikováno v:
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 1:207-215
Inferring user preferences over a set of items is an important problem that has found numerous applications. This work focuses on the scenario where the explicit feature representation of items is unavailable, a setup that is similar to collaborative
Autor:
Hui Jiang, Jinfeng Yin, Fangchao Liu, Yuxia Yao, Chao Cai, Jiying Xu, Lijun Zheng, Chendi Zhu, Junnan Jia, Xu Gao, Wangli Xu, Weimin Li, Guolong Zhang
Publikováno v:
BMC Infectious Diseases, Vol 22, Iss 1, Pp 1-10 (2022)
Abstract Background Recurrence continues to place significant burden on patients and tuberculosis programmes worldwide, and previous studies have rarely provided analysis in negative recurrence cases. We characterized the epidemiological features of
Externí odkaz:
https://doaj.org/article/a034b443956844cfb852427d08bb183b
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 30
Kernel Principal Component Analysis (PCA) is a popular extension of PCA which is able to find nonlinear patterns from data. However, the application of kernel PCA to large-scale problems remains a big challenge, due to its quadratic space complexity
Publikováno v:
KDD
Semi-supervised clustering leverages side information such as pairwise constraints to guide clustering procedures. Despite promising progress, existing semi-supervised clustering approaches overlook the condition of side information being generated s
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 28
Sensitive data such as medical records and business reports usually contains valuable information that can be used to build prediction models. However, designing learning models by directly using sensitive data might result in severe privacy and copy
Comparison of clinical characteristics between COVID-19 and H7N9 fatal cases: An observational study
Autor:
Hui Jiang, Fangchao Liu, Ta-Chien Chan, Jinfeng Yin, Ruowen Huang, Li Shen, Shengjin Tu, Liang Kang, Wen Liu, Na Zhao, Di Zhang, Wangli Xu, Weimin Li, Shelan Liu, Chaolin Huang
Publikováno v:
Frontiers in Public Health, Vol 10 (2022)
ObjectiveThe outbreak of COVID-19 in 2020 is reminiscent of the H7N9 outbreak in 2013, which poses a huge threat to human health. We aim to compare clinical features and survival factors in fatal cases of COVID-19 and H7N9.MethodsData on confirmed CO
Externí odkaz:
https://doaj.org/article/86d793d353e644bdb4baa562cf3a6319
Autor:
Jinfeng Yin, Hongwei Zhang, Zhidong Gao, Hui Jiang, Liyi Qin, Chendi Zhu, Qian Gao, Xiaoxin He, Weimin Li
Publikováno v:
Frontiers in Public Health, Vol 10 (2022)
BackgroundUnderstanding multidrug-resistant tuberculosis (MDR-TB) transmission patterns is crucial for controlling the disease. We aimed to identify high-risk populations and geographic settings of MDR-TB transmission.MethodsWe conducted a population
Externí odkaz:
https://doaj.org/article/e4307e06b3f248ea8ba6637432b308ff