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).

 
 

NEWS

 
Archimedes Flagship Project in Cardiology and AI is Featured in the News!

Archimedes Flagship Project in Cardiology and AI is Featured in the News!

Archimedes Research Unit of the Athena Research Center, Greece, is featured in a recent article in Dnews. This article is about an Archimedes flagship project in cardiology and AI that aims to use "two-dimensional echocardiographic data to develop deep learning tools and improve the treatment of heart problems."

Best Paper Award at FAIEMA 202

Best Paper Award at FAIEMA 202

Vasileios Moustakas, PhD student at the School of Electrical and Computer Engineering - NTUA and Academic Fellow at Archimedes, Athena Research Center, Greece, Konstantinos Cheliotis and Anna Mylona, both MEng students at the School of Electrical and Computer Engineering - NTUA and interns at Archimedes, Athena Research Center, Vassilis Alimisis, Postdoctoral Researcher at Archimedes, Athena Research Center, and Paul Sotiriadis, Lead Researcher at Archimedes, Athena Research Center, and a Professor at the School of Electrical and Computer Engineering - NTUA, received the Best Paper Award (PhD Symposium) at the

Nature Communications Publication on Advanced AI in Biological Research by Giorgos Papanastasiou

Nature Communications Publication on Advanced AI in Biological Research by Giorgos Papanastasiou

Giorgos Papanastasiou, Lead Researcher at the Archimedes Research Unit of the Athena Research Center, Greece,and Faculty Research Fellow at Edinburgh Imaging, at the University of Edinburgh, the Queen’s Medical Research Institute, Edinburgh, UK, has co-published a Nature Communications paper on "Clinical implications of bone marrow adiposity identified by phenome-wide association and Mendelian randomization in the UK Biobank."Prof. Papanastasiou mentions that "this project is a strong testament to the power of augmenting biological research with advanced AI and data science methods."

 
 

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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