Martina Bacaro

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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TAILOR Handbook of Trustworthy AI

The TAILOR Handbook of Trustworthy AI is an encyclopedia of the major scientific and technical terms related to Trustworthy Artificial Intelligence. The main goal of the Handbook of Trustworthy AI is to provide non experts, especially researchers and students, an overview of the problem related to the development of ethical and trustworthy AI systems. The

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Leslie Pack Kaelbling keynote speak at the 2nd TAILOR conference: “Doing for our robots what nature did for us”

Leslie Pack Kaelbling, Panasonic Professor of Computer Science and Engineering at the Department of Electrical Engineering and Computer Science of Massachusetts Institute of Technology, will give a keynote speak at the upcoming TAILOR conference in Prague, on Semptember 13th 2022, 14-15 (CET). Abstract We, as robot engineers, have to think hard about our role in the design

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Impressions from The Joint TAILOR-EurAI Summer school in Barcelona

During the week from 13th to 17th of June, the 19th EurAI Advanced Course on AI (ACAI) and 2nd TAILOR summer school was organised in Barcelona. This joint initiative was devoted to the themes of explainable and trustworthy AI and organized by Carles Sierra and Karina Gibert from the Intelligent Data Science and Artificial Intelligence Research Center at Universitat

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Call for Papers: ACM Computing Surveys – Special Issue on Trustworthy AI

Guest Editors    Roberta Calegari, Alma Mater Studiorum-Università di Bologna, Italy – roberta.calegari@unibo.it      Fosca Giannotti, Scuola Normale Superiore, Italy – fosca.giannotti@isti.cnr.it     Michela Milano, Alma Mater Studiorum-Università di Bologna, Italy – michela.milano@unibo.it     Francesca Pratesi, National Research Council, Italy – francesca.pratesi@isti.cnr.it        This special issue calls for surveys that address at least one dimension of Trustworthy Artificial Intelligence (TAI) and provide a broad and

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Report from Theme Development Workshop “AI for Future Manufacturing”

On the 10th of May 2022, the fourth joint  “Theme Development Workshop” (TDW) focused on the latest trends and challenges of “AI for Future Manufacturing”. The discussion hosted close to 80 key experts from 20 European countries, from both academia and the manufacturing sector, as well as other relevant stakeholders. The participants had one primary, but still very challenging

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Cross-Domain MetaDL: Any-Way Any-Shot Learning Competition with Novel Datasets from Pratical Domains

Meta-learning aims to leverage the experience from previous tasks to solve new tasks using only little training data, train faster and/or get better performance. The proposed challenge focuses on “cross-domain meta-learning” for few-shot image classification using a novel “any-way” and “any-shot” setting. This challenge is part of TAILOR WP2 (see more information here). Goal The

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Accepted papers by TAILOR scientists to IJCAI-ECAI 2022

A lot of TAILOR scientists submitted their paperworks to the 31st International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2022). The conference will be in Vienna, from 23rd to 29th of July, 2022. Here below the (not full) list of accepted papers presented by people involved in TAILOR: AISafety

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