Visiting Researchers’ Presentations

During the two-month summer program we had the opportunity to host talks by visiting researchers that spent some time with us. This provided an opportunity for our PhD fellows and in general the ARCHIMEDES community to get a good understanding of various areas.

Visiting Researchers’ Presentations

Thodoris Lykouris

Efficient Decentralized Multi-Agent Learning in Asymmetric Bipartite Queueing Systems & open directions, networking with speaker

Bailey Flanigan

Better voting via public spirit

Manolis Zampetakis

The Computational Complexity of Finding Stationary Points in Non-Convex Optimization

Vasilis Syrgkanis

Debiased Machine Learning for Static and Dynamic Treatment Settings

Leonidas Guibas

Efficient Neural Scene Representations

Christina Fragouli

Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms

Suhas Diggavi

A Statistical Framework for Private Personalized Federated Learning and Estimation

Giannis Darras

Generative Models and Computational Imaging Soft Diffusion and Learning from Corrupted

Alex Dimakis

Introduction to Diffusion models and Inverse Problems

Ilias Zadik

Computational-Statistical Trade-offs in Group Testing (or: how many “pooled tests” are enough?)

Gustavo Alonso

Modular Data Processing for the Data Science Era

Paolo Papotti

Explainable Fact Checking with Structured Data

Antonis Varvitsiotis

Discovering how agents learn using few data


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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