archimedes-Artificial Intelligence, Data Science, Algorithms-greece

 
Artificial Intelligence
 
Data Science
 
Algorithms

[Archimedes Talks Series] Fuzzy Cognitive Map models for pattern classification and time series forecasting

Dates
2024-07-25 13:00 - 15:30
Venue
Artemidos 1 - Amphitheater

 Title: Fuzzy Cognitive Map models for pattern classification and time series forecasting

Speaker: Gonzalo Nápoles, Assistant Professor at Tilburg University


Abstract: Fuzzy Cognitive Maps (FCMs) are knowledge-based recurrent neural networks originally devoted to modeling and simulating complex systems involving several variables and feedback loops. In these networks, neural concepts represent variables, entities, or states relevant to the physical system being studied. Weights indicate the strength of causality, correlation, or association between the concepts, leading to models that can be deemed interpretable from a static viewpoint. The most prominent characteristic of FCM models is that they allow domain experts to inject knowledge into the model through the weight matrix and concepts’ activation values, thus allowing for hybrid intelligence. Unfortunately, their predictive power had been deemed subpar when compared to other machine learning and deep learning models. In this lecture, I will elaborate on the reasons behind such poor performance and introduce some algorithmic solutions that address this problem to a large extent. In that regard, I will present two FCM-rooted models termed Recurrence-aware Long-term Cognitive Networks and Long Short-term Cognitive Networks, which are oriented to pattern classification and time series forecasting, respectively. While the former is as accurate as black-box machine learning models, the latter often outperforms other deep learning architectures while being up to hundreds of times faster.

 

Bio: Gonzalo Nápoles is a tenured Assistant Professor at the Department of Cognitive Science & Artificial Intelligence, Tilburg University, The Netherlands. My research involves two main directions. The first one involves Neural Cognitive Modeling and its potential for designing interpretable intelligent systems enabling hybrid intelligence. The second one involves Fuzzy Cognitive Mapping applied to fairness research, such as quantifying and mitigating bias.

 

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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 Talk by Manos Athanassoulis on

Archimedes Talk by Manos Athanassoulis on "Harnessing the Untapped Benefits of Near-Sortedness for Data Systems"

On Tuesday 21 October, 2025, from 1:00 pm to 2:00 pm, at the Archimedes Amphitheatre (1 Artemidos Street, 15125, Marousi, Archimedes, Athena Research Center, Greece), Professor Manos Athanassoulis, Associate Professor of Computer Science at Boston University (BU), USA, Director and Founder of the BU Data-intensive Systems and Computing Laboratory, BU, USA, and Co-Director of the BU Massive Data Algorithms and Systems Group, BU, USA, will deliver an Archimedes talk on "Harnessing the Untapped Benefits of Near-Sortedness for Data Systems."

GameSec 2025 just Around the Corner!

GameSec 2025 just Around the Corner!

The 16th Conference on Game Theory and AI for Security (GameSec25), an event strongly supported by Archimedes, Athena Research Center, Greece will take place at the National Technical University of Athens, Greece from October 13-15 2025. "With the rapid advancement of artificial intelligence, game theory, and security technologies, the resilience and trustworthiness of modern systems is more critical than ever. The 2025 Conference on Game Theory and AI for Security focuses on leveraging strategic decision-making, adversarial reasoning, and computational intelligence to address security challenges in complex and dynamic environments.

11 Papers Accepted at NeurIPS 2025!

11 Papers Accepted at NeurIPS 2025!

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

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

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.

 
 

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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