Shagun Sodhani,Meng Qu,Jian Tang
Shagun Sodhani
Network embedding, which aims at learning distributed representations for nodes in networks, is a critical task with wide downstream applications. Most existing studies focus on networks with a single type of edges, whereas in many cases, t...
Chieh-Yang Huang,Hanghang Tong,Jingrui He et al.
Chieh-Yang Huang et al.
Geographic information provides an important insight into many data mining and social media systems. However, users are reluctant to provide such information due to various concerns, such as inconvenience, privacy, etc. In this paper, we ai...
Laura Quitzau Mortensen,Kristoffer Andresen,Jakob Burcharth et al.
Laura Quitzau Mortensen et al.
Matching is frequently used in observational studies, especially in medical research. However, only a small number of articles with matching programs for the SAS software (SAS Institute Inc., Cary, NC, USA) are available, even less are usab...
Dawei Zhou,Lecheng Zheng,Jiejun Xu et al.
Dawei Zhou et al.
Characterizing and modeling the distribution of a particular family of graphs are essential for the studying real-world networks in a broad spectrum of disciplines, ranging from market-basket analysis to biology, from social science to neur...
Qiaoyu Tan,Ninghao Liu,Xia Hu
Qiaoyu Tan
Social network analysis is an important problem in data mining. A fundamental step for analyzing social networks is to encode network data into low-dimensional representations, i.e., network embeddings, so that the network topology structur...
Research Challenges at the Intersection of Big Data, Security and Privacy [0.03%]
大数据、网络安全和隐私保护的挑战研究
Murat Kantarcioglu,Elena Ferrari
Murat Kantarcioglu
Stuart Jackson,Maha Yaqub,Cheng-Xi Li
Stuart Jackson
The continuous delivery of applied machine learning models in healthcare is often hampered by the existence of isolated product deployments with poorly developed architectures and limited or non-existent maintenance plans. For example, actu...
Machine Learning and Artificial Intelligence: Two Fellow Travelers on the Quest for Intelligent Behavior in Machines [0.03%]
机器学习与人工智能：追求智能行为的两位旅伴
Kristian Kersting
Kristian Kersting
Thomas Hartung
Thomas Hartung
Systematic Lab Knowledge Integration for Management of Lipid Excess in High-Risk Patients: Rationale and Design of the SKIM LEAN Project [0.03%]
高危患者的血脂管理(SKIM LEAN项目)：知识整合的合理性和设计
Chiara Pavanello,Marina Parolini,Antonia Alberti et al.
Chiara Pavanello et al.
SKIM LEAN aims at exploiting Electronic Health Records (EHRs) to integrate knowledge derived from routine laboratory tests with background analysis of clinical databases, for the identification and early referral to specialist care, where a...