NSF Student Travel Grant for the 2022 ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022)
NSF 学生旅费资助 2022 年 ACM SIGKDD 知识发现和数据挖掘会议 (KDD 2022)
基本信息
- 批准号:2223561
- 负责人:
- 金额:$ 2.5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-06-15 至 2024-05-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This grant provides support for 25 U.S.-based graduate students to participate in the 28th ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD 2022), which will be held in Washington D.C. from August 14 -18, 2022. KDD is an annual conference that presents the world's premier research in data mining. In the past, the total number of KDD participants has been in excess of 3000. The conference covers topics in the data mining lifecycle, including algorithms, software and systems, and applications. The conference will also focus on related areas such as artificial intelligence, machine learning, data management, and information retrieval. The selection committee will select recipients of the support based on merit and need and place particular emphasis on diversity in the selection process.As an interdisciplinary conference, KDD brings together researchers and practitioners from academia, industry, and governments who work on all aspects of data mining and data science problems. The conference is highly competitive and focuses on training and mentoring students. It includes a technical program with regular peer-reviewed papers in the form of oral and poster presentations, as well as panel discussions and invited talks by leading experts in academia and industry. Besides the technical program, the conference features activities such as workshops, tutorials, panels, posters, project showcases. These will provide a comprehensive multi-facet learning experience to students at all levels. The award will be advertised and the results will be announced at the KDD 2022 website (https://www.kdd.org/kdd2022/) as well as various data mining mailing lists.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
这笔赠款为25个美国-基于研究生参加第28届ACM SIGKDD知识发现和数据挖掘会议(KDD 2022),将于2022年8月14日至18日在华盛顿举行。KDD是一个年度会议,展示了世界上最重要的数据挖掘研究。过去,KDD参与者的总数超过3000人。会议涵盖了数据挖掘生命周期中的主题,包括算法,软件和系统以及应用程序。会议还将关注人工智能、机器学习、数据管理和信息检索等相关领域。KDD是一个跨学科的会议,汇集了来自学术界、工业界和政府的研究人员和从业人员,他们致力于数据挖掘和数据科学问题的各个方面。该会议是高度竞争性的,重点是培训和指导学生。它包括一个技术方案,定期以口头和海报介绍的形式发表同行评审的论文,以及学术界和工业界领先专家的小组讨论和特邀演讲。除了技术计划,会议还包括研讨会、教程、小组讨论、海报、项目展示等活动。这将为各级学生提供全面的多方面学习体验。该奖项将在KDD 2022网站(https://www.kdd.org/kdd2022/)以及各种数据挖掘邮件列表上进行宣传,并公布结果。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Yue Ning其他文献
Track Defect Detection Based on Improved Rtmdet
基于改进Rtmdet的轨道缺陷检测
- DOI:
10.1145/3654823.3654890 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Rong Fan;Qi Sun;Qi He;Zhi Qiao;Hongzhu Chen;Wenqiang Zhao;Lin Ma;Yue Ning;Pengfei Shi - 通讯作者:
Pengfei Shi
Apoptotic Cell-Mediated Immunoregulation of Dendritic Cells Does Not Require iC3b Opsonization1
凋亡细胞介导的树突状细胞免疫调节不需要 iC3b 调理作用1
- DOI:
- 发表时间:
2008 - 期刊:
- 影响因子:4.4
- 作者:
E. Behrens;Yue Ning;Nidal E. Muvarak;P. Zoltick;A. Flake;S. Gallucci - 通讯作者:
S. Gallucci
Exosome-mediated miR-7-5p delivery enhances the anticancer effect of Everolimus via blocking MNK/eIF4E axis in non-small cell lung cancer
- DOI:
https://doi.org/10.1038/s41419-022-04565-7 - 发表时间:
2022 - 期刊:
- 影响因子:
- 作者:
Sile Liu;Weiyuan Wang;Yue Ning;Hongmei Zheng;Yuting Zhan;Haihua Wang;Yang Yang;Jiadi Luo;Qiuyuan Wen;Hongjing Zang;Jinwu Peng;Jian Ma;Songqing Fan - 通讯作者:
Songqing Fan
Simulation of refrigerant-lubricant two-phase flow characteristics and performance test in space compressor
空间压缩机制冷剂-润滑油两相流特性模拟及性能测试
- DOI:
10.1016/j.applthermaleng.2023.120105 - 发表时间:
2023-01 - 期刊:
- 影响因子:6.4
- 作者:
Yilin Ye;Rui Ma;Yue Ning;Yuting Wu - 通讯作者:
Yuting Wu
General and Local: Averaged k-Dependence Bayesian Classifiers (SCI检索)
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:2.7
- 作者:
LiMin Wang;HaoYu Zhao;MingHui Sun;Yue Ning - 通讯作者:
Yue Ning
Yue Ning的其他文献
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{{ truncateString('Yue Ning', 18)}}的其他基金
CAREER: Towards Deep Interpretable Predictions for Multi-Scope Temporal Events
职业:对多范围时间事件进行深度可解释的预测
- 批准号:
2047843 - 财政年份:2021
- 资助金额:
$ 2.5万 - 项目类别:
Continuing Grant
CRII: III: Learning Dynamic Graph-based Precursors for Event Modeling
CRII:III:学习基于动态图的事件建模前体
- 批准号:
1948432 - 财政年份:2020
- 资助金额:
$ 2.5万 - 项目类别:
Standard Grant
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