1 code implementation • 23 Mar 2020 • Caleb Belth, Xinyi Zheng, Jilles Vreeken, Danai Koutra
We apply our rules to three large KGs (NELL, DBpedia, and Yago), and tasks such as compression, various types of error detection, and identification of incomplete information.
1 code implementation • 27 Jun 2020 • Caleb Belth, Xinyi Zheng, Danai Koutra
Frequent pattern mining is a key area of study that gives insights into the structure and dynamics of evolving networks, such as social or road networks.
no code implementations • 1 May 2020 • Xinyi Zheng, Doug Burdick, Lucian Popa, Xu Zhong, Nancy Xin Ru Wang
With GTE-Table, we invent a new penalty based on the natural cell containment constraint of tables to train our table network aided by cell location predictions.
no code implementations • 23 May 2020 • Yixian Zhang, Jieren Chen, Boyi Liu, Yifan Yang, Haocheng Li, Xinyi Zheng, Xi Chen, Tenglong Ren, Naixue Xiong
With the spread and development of new epidemics, it is of great reference value to identify the changing trends of epidemics in public emotions.
no code implementations • WS 2020 • Nikita Bhutani, Xinyi Zheng, Kun Qian, Yunyao Li, H. Jagadish
Knowledge-based question answering (KB{\_}QA) has long focused on simple questions that can be answered from a single knowledge source, a manually curated or an automatically extracted KB.
no code implementations • 8 Jun 2022 • Xinyi Zheng, Ryan A. Rossi, Nesreen Ahmed, Dominik Moritz
Challenges arise as networks are often used across different domains (e. g., network science, physics, etc) and have complex structures.
no code implementations • 26 Apr 2023 • Xinyi Zheng, Weijie Zhao, Xiaoyun Li, Ping Li
To retrieve personalized campaigns and creatives while protecting user privacy, digital advertising is shifting from member-based identity to cohort-based identity.
no code implementations • 21 Jul 2023 • Diana M. Negoescu, Humberto Gonzalez, Saad Eddin Al Orjany, Jilei Yang, Yuliia Lut, Rahul Tandra, Xiaowen Zhang, Xinyi Zheng, Zach Douglas, Vidita Nolkha, Parvez Ahammad, Gennady Samorodnitsky
We introduce Epsilon*, a new privacy metric for measuring the privacy risk of a single model instance prior to, during, or after deployment of privacy mitigation strategies.