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Artificial Intelligence
 
Data Science
 
Algorithms

[Archimedes Talks Series]Efficiently Certifiable Guarantees for Learning with Distribution Shift

Dates
2025-01-08 14:30 - 16:00
Venue
Artemidos 1 - Amphitheater
TITLE: Efficiently Certifiable Guarantees for Learning with Distribution Shift

SPEAKER: Kostas Stavropoulos (Ph.D. student in Computer Science at UT Austin)

ABSTRACT: Learning in the presence of distribution shift remains a major and challenging problem in machine learning. In this setting, the learner is trained on some labeled training distribution, but evaluated on some other, potentially adversarial, test distribution for which the learner only has unlabeled examples. A long series of works in the past twenty years has focused on giving bounds for the test error in terms of appropriate notions of distance between the training and test distributions. Such distances, however, typically involve enumerations and no efficient algorithms for estimating or even testing such distances are available.

In this talk, we present a new model called testable learning with distribution shift, where the learner is allowed to reject, but only if distribution shift is detected. If the learner accepts, then the output hypothesis is guaranteed to have low test error. In this framework, we provide the first efficient algorithms for learning several fundamental concept classes in the presence of distribution shift under standard assumptions on the training marginal distribution. The classes we capture include halfspace intersections, decision trees and, in general, any class that admits low-degree sandwiching approximators.

REFERENCES: https://arxiv.org/abs/2311.15142 , https://arxiv.org/abs/2404.02364 , https://arxiv.org/abs/2406.09373 , https://arxiv.org/abs/2406.02742 

SHORT BIO: Kostas Stavropoulos ( https://www.kstavrop.com ) is currently a fourth-year Ph.D. student in Computer Science at UT Austin. He is fortunate to be advised by Prof. Adam Klivans. Before that, he studied Electrical and Computer Engineering at the National Technical University of Athens, where he was fortunate to work with Prof. Dimitris Fotakis. His research is in the intersection of machine learning and theoretical computer science. He is particularly interested in designing efficient learning algorithms with provable guarantees that do not rely on the strong assumptions typically made in learning theory, especially in challenging scenarios like learning with distribution shift and/or noise.


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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

 
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11 Papers Accepted at NeurIPS 2025!

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We are happy to announce that 11 papers from Archimedes, Athena Research Center, Greece, have been accepted at the Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025)!NeurIPS is a major annual event in the artificial intelligence and machine learning community and this year it will take place from December 2 to December 7 at the San Diego Convention Center, California, USA.

Archimedes Postdoc will Conduct a Tutorial at the International Conference on Microelectronics 2025

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6 October 2025

Vassilis Alimisis, a postdoctoral researcher at Archimedes, Athena Research Center, Greece, will deliver a tutorial on "Low-Power Analog Hardware Classifier Architecture for ML Applications: From A to Z" at the International Conference on Microelectronics (ICM 2025), taking place on 14-17 December, 2025, in Cairo, Egypt.Abstract: This tutorial provides a comprehensive introduction to the design and implementation of low-power analog hardware classifiers tailored for machine learning (ML) applications, with a focus on energy-constrained environments such as edge devices and biomedical wearables. With the growing need for fast, efficient, and real-time data processing, analog computing has re-emerged as a promising solution that enables in-memory computation and significantly reduces power consumption compared to conventional digital processors.

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

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

30 September 2025

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."This project will be developed in collaboration with the Onassis Cardiac Surgery Center and the Archimedes Research Unit of the Athena Research Center, Greece. The Onassis Cardiac Surgery Center will contribute cardiac data and medical expertise, while the Archimedes Research Unit will set up a team of researchers who will develop advanced techniques and AI models that will address specific cardiological issues.

More news items here
 
 

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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