Balancing Gender Bias in Job Advertisements With Text-Level Bias Mitigation [0.03%]
利用文本级偏见缓解平衡工作广告中的性别偏见
Shenggang Hu,Jabir Alshehabi Al-Ani,Karen D Hughes et al.
Shenggang Hu et al.
Despite progress toward gender equality in the labor market over the past few decades, gender segregation in labor force composition and labor market outcomes persists. Evidence has shown that job advertisements may express gender preferenc...
Roberto Grasso,Giovanni Micale,Alfredo Ferro et al.
Roberto Grasso et al.
Temporal networks are graphs where each edge is linked with a timestamp, denoting when an interaction between two nodes happens. According to the most recently proposed definitions of the problem, motif search in temporal networks consists ...
Surya Nepal,Ryan K L Ko,Marthie Grobler et al.
Surya Nepal et al.
An Experimental Study on the Scalability of Recent Node Centrality Metrics in Sparse Complex Networks [0.03%]
稀疏复杂网络中最近节点中心性度量的可扩展性研究
Alexander J Freund,Philippe J Giabbanelli
Alexander J Freund
Node centrality measures are among the most commonly used analytical techniques for networks. They have long helped analysts to identify "important" nodes that hold power in a social context, where damages could have dire consequences for t...
Daily Spatial Complete Soil Moisture Mapping Over Southeast China Using CYGNSS and MODIS Data [0.03%]
基于CYGNSS和MODIS数据的中国东南地区土壤墒情的日变化空间制图研究
Ting Yang,Zhigang Sun,Jundong Wang et al.
Ting Yang et al.
Daily spatial complete soil moisture (SM) mapping is important for climatic, hydrological, and agricultural applications. The Cyclone Global Navigation Satellite System (CYGNSS) is the first constellation that utilizes the L band signal tra...
Development of a Machine Learning Approach for Local-Scale Ozone Forecasting: Application to Kennewick, WA [0.03%]
一种局部尺度预报地面臭氧的机器学习方法的发展及其在华盛顿州肯纳威克市的应用研究
Kai Fan,Ranil Dhammapala,Kyle Harrington et al.
Kai Fan et al.
Chemical transport models (CTMs) are widely used for air quality forecasts, but these models require large computational resources and often suffer from a systematic bias that leads to missed poor air pollution events. For example, a CTM-ba...
Domenico Talia,Paolo Trunfio,Jesus Carretero et al.
Domenico Talia et al.
Automated Detection of Vaping-Related Tweets on Twitter During the 2019 EVALI Outbreak Using Machine Learning Classification [0.03%]
机器学习分类在2019年EVALI疫情期间自动检测推特上的与电子烟相关的推文
Yang Ren,Dezhi Wu,Avineet Singh et al.
Yang Ren et al.
There are increasingly strict regulations surrounding the purchase and use of combustible tobacco products (i.e., cigarettes); simultaneously, the use of other tobacco products, including e-cigarettes (i.e., vaping products), has dramatical...
Ruixiang Tang,Ninghao Liu,Fan Yang et al.
Ruixiang Tang et al.
Explainable machine learning attracts increasing attention as it improves the transparency of models, which is helpful for machine learning to be trusted in real applications. However, explanation methods have recently been demonstrated to ...
Nithin Govindarajan,Nico Vervliet,Lieven De Lathauwer
Nithin Govindarajan
We introduce a supervised learning framework for target functions that are well approximated by a sum of (few) separable terms. The framework proposes to approximate each component function by a B-spline, resulting in an approximant where t...