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TRIPODS: Institute for Foundations of Data Science (IFDS)

TRIPODS: Institute for Foundations of Data Science (IFDS)
TRIPODS:数据科学研究所 (IFDS)
批准号:
1740751
负责人:
Piotr Indyk
金额:
$136.85万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-10-01 至 2021-09-30

项目摘要

项目成果

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中文摘要
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英文摘要
The aim of this project is to plant the seeds for an interdisciplinary institute devoted to foundations of data science at MIT. During the three years of Phase I, the project goal is to stimulate research and educational interactions between mathematics, statistics and theoretical computer science, both within MIT and in the research community at large. On the way, the team will also develop the organizational capabilities and visibility needed for the (potential) Phase II activities.The project activities in Phase I will be organized around 5 semester-long themes. Each theme will be devoted to a topic at the intersection of at least two (and often three) TRIPODS areas, and will focus on catalyzing interactions between them. The specific themes are: statistical and computational tradeoffs, sub-linear algorithms and distribution testing, learning with complex structures, graphical models and exchangeability, and non-convex optimization. Within each theme, the PIs will organize numerous activities, including a workshop, a fall/spring school covering introductory material, and regular seminars. They will also support knowledge transfer activities, including office hours that will offer free help and consultation on algorithmic, mathematical and statistical aspects of data science. To facilitate the interactions between the participants, the project will support two project postdocs, who will play the role of connectors between different disciplines.
期刊论文(65)
专著(0)
科研奖励(0)
会议论文
Model Agnostic Time Series Analysis via Matrix Estimation
通过矩阵估计进行与模型无关的时间序列分析
DOI: 10.1145/3287319
发表时间: 2018
期刊: Proceedings of the ACM on Measurement and Analysis of Computing Systems
影响因子: --
作者: [Agarwal, Anish, Amjad, Muhammad Jehangir, Shah, Devavrat, Shen, Dennis]
通讯作者: Shen, Dennis
Monotone probability distributions over the Boolean cube can be learned with sublinear samples
布尔立方体上的单调概率分布可以通过次线性样本来学习
DOI: --
发表时间: 2020
期刊: 11th Innovations in Theoretical Computer Science (ITCS 2020
影响因子: --
作者: [Rubinfeld, Ronitt, Vasilyan, Arsen]
通讯作者: Vasilyan, Arsen
DOI: 10.1016/j.cell.2019.01.006
发表时间: 2019-02-07
期刊: CELL
影响因子: 64.5
作者: [Schiebinger, Geoffrey, Shu, Jian, Lander, Eric S.]
通讯作者: Lander, Eric S.
DOI: 10.1073/pnas.1917151117
发表时间: 2020-06
期刊: Proceedings of the National Academy of Sciences
影响因子: --
作者: [Subhro Ghosh;P. Rigollet]
通讯作者: Subhro Ghosh;P. Rigollet
62
    Travel: SODA 2024 Conference Student and Postdoc Travel Support
    Conference: SODA 2023 Conference Student and Postdoc Travel Support
    Foundations of Data Science Institute
    Collaborative Research: AF: Small: Fine-Grained Complexity of Approximate Problems
    海外基金