Artificial Intelligence
Data Science
Algorithms
archimedes-Artificial Intelligence, Data Science, Algorithms-greece
greece
Algorithms
Data Science
Artificial Intelligence
[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
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).
Christos Papadimitriou Speaks on “Artificial Intelligence: its History, its Present, and its Uncertain Future”
24 March 2026
Christos Papadimitriou, Donovan Family Professor of Computer Science at Columbia Engineering at Columbia University, USA, and Principal Scientist at the Archimedes Research Unit of the Athena Research Center, Greece, spoke about “Artificial Intelligence: its History, its Present, and its Uncertain Future” during the ten-year anniversary event of diaNEOsis think tank, which took place on March 11, 2026, at the Stavros Niarchos Foundation Cultural Center (SNFCC).
Vasia Papanikou to Present the MIMOSA Fairness Exploration Tool at EDBT/ICDT 2026 Joint Conference
24 March 2026
Vasia Papanikou, a PhD student at the University of Ioannina and an Academic fellow at Archimedes, Athena Research Center, Greece, will be demonstrating "MIMOSA: A Tool for Fairness Exploration Through Explanations" at the 29th International Conference on Extending Database Technology (EDBT/ICDT 2026), taking place from March 24–27, 2026, at Tampere, Finland.
Archimedes Academic Fellow Andreas Lolos Presents Research at WACV 2026
16 March 2026
Archimedes Academic Fellow and a third-year PhD student at the National and Kapodistrian University of Athens in Greece, Andreas Lolos recently travelled to Tucson in Arizona, USA, and presented the paper "SGPMIL: Sparse Gaussian Process Multiple Instance Learning" at the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2026).
6 Accepted Papers at ICLR 2026
11 March 2026
The Archimedes research unit of the Athena Research Center in Greece has six papers accepted at this year's International Conference on Learning Representations (ICLR) gathering, including one oral presentation. The acceptance rate for posters was about 25,8% and about 1,1% for oral presentations. Please bear in mind that ICLR, along with NeurIPS and ICML, is considered one of the three top-tier artificial intelligence and machine learning conferences in the world.
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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