Connectivity Fund

CLAIRE | Rising Research Network: AI Research and Mental Well-Being Workshop

Nicolò Brandizzi PhD student at Sapienza University of Rome Abstract The rapid advancements in artificial intelligence (AI) research and applications have emphasized the need for collaboration between academia and industry, especially among new AI researchers. Such collaborations drive innovation, translate research into practical solutions, and address sector-specific challenges. The CLAIRE Rising Researcher Network (R2Net) aims […]

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Fostering Appropriate Trust in Predictive Policing AI Systems

Siddharth Mehrotra PhD student at TU Delft The use of AI in law enforcement, particularly in predictive policing, raises concerns about bias, discrimination, and infringement of civil liberties. Building appropriate trust in these systems is crucial to address these concerns and ensure ethical use. In this research proposal, we aim to investigate how explanations generated

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Meta-learning for Continual Learning

Anna Vettoruzzo PhD student at the Halmstad University Continual learning (CL) refers to the ability to continually learn over time by accommodating new knowledge while retaining previously learned experiences. While this concept is inherent in the human learning ability, current machine learning-based methods struggle with this as they are highly prone to forget past experiences

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Deep reinforcement learning for predictive monitoring under LTLf constraints

Efrén Rama Maneiro PhD student at the University of Santiago de Compostela Predictive monitoring is a subfield of process mining that focuses on predicting how a process will unfold. Deep learning techniques have become popular in this field due to their enhanced performance with respect to classic machine learning models. However, most of these approaches

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Data-Centric AutoML and Benchmarks with Optimal Transport

Prabhant Singh Research Engineer at TU Eindhoven Automated machine learning (AutoML) aims to make easier and more accessible use of machine learning algorithms for researchers with varying levels of expertise. However, AutoML systems, including classical ones such as Auto-Sklearn and Neural Architecture Search (NSGANet, ENAS, DARTS), still face challenges with starting from scratch for their

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Multi-Objective Rating Systems

Paolo Turrini Associate Professor at the Department of Computer Science, University of Warwick This project studies rating systems with multiple objectives, where users are matched to items in order to satisfy several desirable properties. In particular, it looks beyond classical Pareto efficiency, modelling and studying allocations that satisfy fairness, diversity and reliability. This project will

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Optimal training of a structured ensemble of Binarized Neural Networks with Mixed-Integer Linear Programming techniques

Simone Milanesi, Ambrogio Maria Bernardelli PhD students at the CompOpt Lab (University of Pavia) Binarized Neural Networks (BNNs) are receiving increasing attention due to their lightweight architecture and ability to run on low-power devices.The Mixed-Integer Linear Programming (MILP) approach achieves the state of the art for training classification BNNs when limited data are available.We propose

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Open Machine Learning workshop

Meelis Kull Associate Professor at the University of Tartu he field of Machine Learning continues to grow tremendously and has a significant impact on society. As such, it is important to democratize machine learning, i.e. to make sure that software, datasets, models, and analyses are freely available for easy discovery, verifiability, reproducibility, reuse and meta-analysis.

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Predicting conversational memorability in group interactions: Continual learning approach

Maria Tsfasman PhD student at TU Delft As AI applications continue to proliferate in our daily lives, the need for social intelligence in these systems becomes increasingly crucial. To enable long-term performance of social intelligence, AI systems must be aware of important moments, or “hotspots” in user conversations. Till now, conversational hotspots have been mainly

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Mastering Natural Language Processing methodologies and technologies

Mariangela Graziano PhD student at Università degli Studi della Campania “L. Vanvitelli” Natural Language Processing (NLP) is an area of artificial intelligence (AI) that deals with giving computers the ability to understand text and spoken words in the same way that people do. As textual data is now everywhere: documents on our PCs or in

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