archimedes-Artificial Intelligence, Data Science, Algorithms-greece

 
Artificial Intelligence
 
Data Science
 
Algorithms

[Archimedes Talks Series] Counting Stars is Constant-Degree Optimal For Detecting Any Planted Subgraph

Dates
2024-07-11 17:00 - 18:00
Venue
Microsoft Teams Meeting
Title: Counting Stars is Constant-Degree Optimal For Detecting Any Planted Subgraph

Presenter: Professor Ilias Zadik, Assistant Professor at Yale University


Abstract: Over the last decade, multiple papers have studied the power of low-degree polynomials in detecting subgraphs in random graphs. Formally, all these papers study special cases of the following general hypothesis testing problem: let H=H_n be an arbitrary undirected graph on n vertices. Can a D-degree polynomial detect between a ``null'' Erdős-Rényi random graph G(n,p) and a ``planted'' random graph which is the union of G(n,p) together with a random copy of H=H_n? The special cases include the case when H is a clique (the planted clique model), when  H is a matching (the planted matching problem), and more.
 
We prove a new unifying positive result that for all H=H_n, as long as D=O(1), the optimal such D-degree polynomial is always given simply by the count stars in the input graph. This allows us to prove multiple old and new results in the literature of low-degree polynomials for this task.

Bio: Ilias Zadik is Assistant Professor of Statistics and Data Science at Yale University. His research mainly focuses on the mathematical theory of statistics and its many connections with other fields such as computer science, probability theory, and statistical physics. His primary area of interest is the study of “computational-statistical trade-offs,” where the goal is to understand whether computational bottlenecks are unavoidable in modern statistical models or a limitation of currently used techniques. Prior to Yale, he held postdoctoral positions at MIT and NYU. He received his PhD from MIT in 2019. 


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Vision

To position Greece as a leading player in AI and Data Science

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Mission

To build an AI Excellence Hub in Greece where the international research community can connect, groundbreaking ideas can thrive, and the next generation of scientists emerges, shaping a brighter future for Greece and the world

 

Welcome to ARCHIMEDES, a vibrant research hub connecting the global AI and Data Science research community fostering groundbreaking research in Greece and beyond. Its dedicated core team, comprising lead researchers, affiliated researchers, Post-Docs, PhDs and interns, is committed to advancing basic and applied research in Artificial Intelligence and its supporting disciplines, including Algorithms, Statistics, Learning Theory, and Game Theory organized around 8 core research areas. By collaborating with Greek and Foreign Universities and Research Institutes, ARCHIMEDES disseminates its research findings fostering knowledge exchange and providing enriching opportunities for students. Leveraging AI to address real-world challenges, ARCHIMEDES promotes innovation within the Greek ecosystem and extends its societal impact. Established in January 2022, as a research unit of the Athena Research Center with support from the Committee Greece 2021, ARCHIMEDES is funded for its first four years by the EU Recovery and Resilience Facility (RRF).

 
 

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The project “ARCHIMEDES Unit: Research in Artificial Intelligence, Data Science and Algorithms” with code OPS 5154714 is implemented by the National Recovery and Resilience Plan “Greece 2.0” and is funded by the European Union – NextGenerationEU.

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