Statistics in the Big Data Era
Statistics in the Big Data Era
批准号:
2005243
负责人:
Peng Ding
金额:
$2.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-01-01 至 2022-12-31
关键词:
中文摘要
点击翻译按钮获取中文摘要
英文摘要
This award supports participation by graduate students and junior researchers in the conference "Statistics in the Big Data Era" held at the Simons Institute for the Theory of Computing at the University of California, Berkeley during May 27-29, 2020. This conference focuses on the changing role and nature of the discipline of statistics in the time of a data deluge in many applications, and on the increasing success of artificial intelligence at performing many data analysis tasks. The conference will feature approximately twenty invited speakers who have made fundamental contributions to the theory and practice of statistics and machine learning. The meeting aims to bring together experts in statistical methodology and theory for complex and big data with researchers focused on a range of applications, from genomics to social networks, and to provide opportunities for early-career researchers to learn about both emerging methods and applications. This conference will be an especially important opportunity for graduate students and early-career researchers to see recent advances and emerging challenges in the theory, methodology, and application of statistics in the big data era.Statistics plays a central role in quantitative research in many disciplines, including social and biological sciences. With the advances in information technology, statistics has gone through a paradigm shift from conventional methods to big data analytics and modern machine learning. This conference will bring together current leading statisticians and the next generation of statistical leaders to discuss achievements and difficulties in the statistical analysis of big data. The meeting will focus on methodology for solving challenges involving big data with complex and heterogeneous structure. The discussions will promote opportunities for statisticians to identify important research topics and critical applications in science and industry. Another important component is a poster session in which students and early-career researchers present their work. The conference program also includes discussion of statistics and data science education in the era of big data.More information about the conference can be found at https://simons.berkeley.edu/workshops/statistics-big-data-era.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.
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CAREER: The Design-Based Perspective of Causal Inference in Complex Experiments
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批准号:1945136
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项目类别:Continuing Grant
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资助金额:$40.0万
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财政年份:2020
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负责人:Peng Ding
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依托单位:
RTG: Advancing Machine Learning - Causality and Interpretability
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批准号:1745640
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项目类别:Continuing Grant
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资助金额:$190.82万
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财政年份:2018
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负责人:Peng Ding
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依托单位:
Collaborative Research: Theoretical and Methodological Frameworks for Causal Inference of Peer Effects
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批准号:1713152
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项目类别:Standard Grant
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资助金额:$18.0万
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财政年份:2017
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负责人:Peng Ding
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依托单位:
国内基金
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