archimedes-Artificial Intelligence, Data Science, Algorithms-greece

 
Artificial Intelligence
 
Data Science
 
Algorithms

[Archimedes Talks Series] Combinatorial Selection with Costly Information

Dates
2024-12-18 14:30 - 16:00
Venue
Artemidos 1 - Amphitheater
TITLE: Combinatorial Selection with Costly Information


ABSTRACT: We consider a class of optimization problems over stochastic variables where the algorithm can learn information about the value of any variable through a series of costly steps; we model this information acquisition process as a Markov Decision Process (MDP). The algorithm’s goal is to minimize the cost of its solution plus the cost of information acquisition, or alternately, maximize the value of its solution minus the cost of information acquisition. Such bandit superprocesses have been studied previously but solutions are known only for fairly restrictive special cases.
We develop a framework for approximate optimization of bandit superprocesses that applies to arbitrary processes with a matroid (and in some cases, more general) feasibility constraint. Our framework establishes a bound on the optimal cost through a novel cost amortization; it then couples this bound with a notion of local approximation that allows approximate solutions for each component MDP in the superprocess to be composed without loss into a global approximation.
We use this framework to obtain approximately optimal solutions for several variants of bandit superprocesses for both maximization and minimization. We obtain new approximations for combinatorial versions of the previously studied Pandora’s Box with Optional Inspection and Pandora’s Box with Partial Inspection; as well as approximation algorithms for a new problem that we call the Weighing Scale problem.


SHORT BIO: Dimitrios (aka Dimitris) Christou ( https://dblp.org/pid/244/9936.html ) is a fourth year Computer Science PhD student at UT Austin. He is fortunate to be advised by Prof. Shuchi Chawla. Prior to joining UT Austin, he received a Diploma in Electrical and Computer Engineering from the National Technical University of Athens, supervised by Prof. Dimitris Fotakis. He has completed two research internships offered by the LIP6 Research Institute at Sorbonne University, France. His research interests lie in the intersection of Online Algorithms, Data-Driven algorithmic design and Operations Research.

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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 Workshop on Dialect NLP

Archimedes Workshop on Dialect NLP

Upcoming workshop on Dialect NLP on “Standardization and Variation for Dialect Varieties with Universal Dependencies as an Application Framework” coming up. We are excited to announce that the Dialect NLP team at Archimedes, Athena Research Center, Greece, is organizing a workshop in collaboration with the MaiNLP Research Lab at Ludwig Maximilian University (LMU) of Munich. Workshop details:Workshop info: UniDive WG1 Workshop on Dialect Varieties Dates: September 5–6, 2025 Location: LMU Munich Funded by: UniDive – Universality, Diversity and Idiosyncrasy in Language Technology Archimedes: Dialect NLP and Linguistic Diversity At Archimedes, our Dialect NLP team focuses on the intersection of AI and linguistic diversity, with an emphasis on under-resourced and endangered language varieties, both Greek and non-Greek. Our research includes:   • Dialectal speech-to-text and morphosyntactic modeling  • Dialect-to-standard normalization for Greek varieties   • Intra-dialectal variation analysis   • A critical perspective on annotation frameworks like Universal Dependencies (UD), especially when applied to non-standard or endangered varieties Our resources cover:   • Standard Modern Greek: GUD Treebank   • Greek dialects: Cretan, Messinian, Lesbian, Cypriot, Griko/Greko, Aperathitika   • Non-Greek varieties spoken in Greece: Pomak, Arvanitika All datasets, models, and tools we develop are freely available to the research community. About Our Collaborators at MaiNLP (LMU Munich) The MaiNLP Research Lab at Ludwig-Maximilians-Universität Munich conducts research in Natural Language Processing, combining computer science, linguistics, and cognitive science. Their focus is on human-facing NLP: developing models that are robust to variation, fair, and reflective of human annotation diversity. MaiNLP is also leading the ERC Consolidator Grant project DIALECT, which explores natural language understanding for non-standard languages and dialects—making them an ideal partner in our shared mission to design NLP systems that work for all language varieties. Workshop Goals This workshop will:   • Document current practices in dialectal UD treebanks (e.g., orthographic/phonological variation, lemmatization, interference)   • Identify gaps in annotation and processing across dialects   • Develop shared methodologies for handling variation, improving consistency, and enabling knowledge transfer   • Foster community engagement with researchers working on under-resourced dialects and less-studied language families   • Ground discussions in theoretical insights from Plank (2016): What to do about non-standard language in NLP It is an opportunity to reflect on how annotation frameworks and tools serve—or fall short of serving— dialectal and endangered varieties, and how AI can support documentation, analysis, and preservation of linguistic diversity. We look forward to sharing our findings and engaging with colleagues working on inclusive, culturally informed, and variation-aware NLP. Stay tuned for more updates!

Archimedes and the Biomedical Research Foundation Share Latest Findings in AI and Medicine

Archimedes and the Biomedical Research Foundation Share Latest Findings in AI and Medicine

Archimedes and the Biomedical Research Foundation of the Academy of Athens successfully hosted a special collaborative session at the Panhellenic Working Group Seminars of the Hellenic Society of Cardiology. This session focused on innovative applications of artificial intelligence in medicine, with a particular emphasis on advancements in cardiology. Held on Friday, February 7, 2025, in Room MC2 of the Megaron Athens International Conference Centre, the event brought together leading experts to explore how artificial intelligence is transforming cardiovascular medicine.

Archimedes Reaches Milestone of 200 Publications

Archimedes Reaches Milestone of 200 Publications

Archimedes is proud to announce that its researchers have published over 200 scientific publications in top-tier conferences (NeurIPS, ICLR, ICML) and journals.Archimedes maintains a vibrant scientific community of over 130 researchers, including more than 60 senior researchers (faculty members from Greece and abroad), 12 postdoctoral fellows, and 55 PhD students, along with over 20 undergraduate interns from various disciplines.

 
 

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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