Connectivity Fund

Multi-Objective Statistically Robust Algorithm Ranking

Jeroen G. Rook – University of Twente PhD candidate Comparing algorithms is a non-trivial task. Often, a set of representative problem instances are used to compare algorithms. However, these problem instances introduce biases in the comparison outcomes, which is often not taken into account. The confidence of the comparison can be strengthened by using statistical …

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Deep fake videos detection through Explainable AI

Aiming towards combating the challenges faced by fake video detection, the prime objective of this research is to develop a proactive, advanced explainable, human collaborated AI-based online disinformation detecting tool for securing a trustworthy social media environment.

Modeling others for cooperation under imperfect information

Nieves Montes PhD Student at Artificial Intelligence Research Institute (IIIA-CSIC) This research visit will focus on models for empathetic software agents. This means embedding autonomous agents with the ability to model their peers and understand the reasons behind their behaviour. This work is to enhance the performace of agents in cooperative tasks, where they need …

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Conformal Inference for multivariate, complex, and heterogeneous data

Marcos Matabuena University of Santiago de Compostela In this project, in collaboration with Gábor Lugosi (UPF), we propose new uncertainty quantification methods based on the design of new Conformal Inference strategies for complex data that arise in modern personalized medicine applications. The new uncertainty methods can examine the reliability and safety of results obtained with …

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Private Continual Learning from a Stream of Pretrained Models

Antonio Carta Post-doc at Pisa University Learning continually from non-stationary data streams is a challenging research topic of growing popularity in the last few years. Being able to learn, adapt and generalize continually, in an efficient, effective and scalable way appears to be fundamental for a more sustainable development of Artificial Intelligent systems. However, access …

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Matheuristic Techniques for Timetabling Problems

Roberto Maria Rosati PhD Student in Information Engineering at University of Udine Recently, matheuristics have emerged as a promising research branch in combinatorial optimization. Thanks to this collaboration supported by TAILOR connectivity fund, we will design and apply novel matheuristic techniques to a variety of timetabling problems that are under investigation at University of Udine. …

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1st International Joint Conference on Learning & Reasoning

Nikos Katzouris National Center for Scientific Research “Demokritos” The rapid progress in machine learning has been the primary reason for a fresh look in the transformative potential of AI as a whole during the past decade. A crucial milestone for taking full advantage of this potential is the endowment of algorithms that learn from experience …

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Trustworthy and sample efficient computer vision

Mohammadreza Amirian Research assistant, Zurich University of Applied Sciences (ZHAW) After the breakthrough of transformers in the context of natural language processing, these models are now being adapted for computer vision and image classification tasks. Transformer-based models showed at least equal descriptive properties compared with convolutional models, however, initial specimen required a larger amount of …

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