archimedes-Artificial Intelligence, Data Science, Algorithms-greece

 
Artificial Intelligence
 
Data Science
 
Algorithms

[Archimedes Talks Series] From Hierarchical Clustering to Phylogenetic CSPs, in the worst-case and beyond

Dates
2024-07-26 13:30 - 15:00
Venue
Artemidos 1 - Amphitheater
Title: From Hierarchical Clustering to Phylogenetic CSPs, in the worst-case and beyond

Speaker: Vaggos Chatziafratis, Assistant Professor of Computer Science & Engineering at the University of California


Abstract: Hierarchical Clustering (HC) is a widely studied problem in unsupervised learning and exploratory data analysis, usually tackled by simple agglomerative procedures like average-linkage, single-linkage or complete-linkage. Applications of HC include reasoning about text documents, understanding the Evolution of species and the Tree of life, decomposing social networks like Facebook, or even organizing large data centers efficiently. Surprisingly, despite the plethora of heuristics for tackling the problem, until recently there was no optimization objective associated with it; this is in stark contrast with flat clustering objectives like k-means, k-median and k-center. In this talk, we will give an overview of the optimization objectives for Hierarchical Clustering, we will discuss connections to Phylogenetic and Triplet/Quartet Reconstruction methods, we will see some simple algorithms to find approximate solutions, and finally we will discuss some recent hardness of approximation results and new connections to the notion of approximation resistance of CSPs. 

Bio: Vaggos Chatziafratis is an Assistant Professor of Computer Science & Engineering at the University of California in Santa Cruz, where he is part of the Theoretical Computer Science group. His research lies at the intersection of approximation algorithms and machine learning, focusing on the design and analysis of approximation algorithms/hardness for clustering problems, and on understanding neural networks through the lens of dynamical systems. Vaggos completed his MS and PhD at Stanford University in the Computer Science Department, where he was advised by Tim Roughgarden and Moses Charikar. Before Stanford, he finished with a Diploma from the ECE department of the National Technical University of Athens. Before joining UC Santa Cruz, he did a postdoc at Google Research under Vahab Mirrokni and Mohammad Mahdian. He also did a postdoc at Northwestern under Konstantin Makarychev, Aravindan Vijayaraghavan and Samir Khuller. Vaggos is the recipient of a FODSI postdoc fellowship at MIT (under Piotr Indyk) and Northeastern. His research at UCSC has been supported by a Hellman Fellowship.

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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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Archimedes Reaches Milestone of 200 Publications

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Happy International Greek Language Day!

Happy International Greek Language Day!

Today, we celebrate the historical, cultural, and linguistic significance of the Greek language. While Standard Modern Greek often takes center stage, we at Archimedes - AI and Data Science Research Hub recognize the impressive diversity and great cultural significance of its numerous dialects. These dialects present both exciting opportunities and complex challenges for AI and Large Language Models (LLMs) because each one of them presents unique linguistic features and all of them are low resourced. That’s why we’re using cutting-edge AI to document, digitize, and analyze these invaluable linguistic treasures, ensuring their preservation and accessibility for generations to come.

Two Research Positions in Data Stream Management Systems & Big Data Management

Two Research Positions in Data Stream Management Systems & Big Data Management

We are pleased to announce the availability of two research positions in data stream management systems and big data management, to be co-supervised by Assistant Professor Odysseas Papapetrou from the Eindhoven University of Technology (TU/e) in the Netherlands and Professor Minos Garofalakis from the Technical University of Crete in Greece.

 
 

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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