September 2022

New projects funded by Connectivity Fund

Also for this call, Connectivity Fund received many applications. We are glad to announce the funded projects for this session: For having a look to the other projects granted by Connectivity Fund, check this webpage: https://tailor-network.eu/connectivity-fund/funded-projects/ The next call for Connectivity Fund will be in 4 months. The next deadline is in 15th of March […]

New projects funded by Connectivity Fund Read More »

A Modular Framework for Hybrid Participatory Systems

Enrico Liscio – TU Delft PhD student Participatory systems aim to elicit citizens’ stances on societal discussions to inform policy making. In particular, human values are a crucial component of citizens’ stances, since they are the drivers of our opinions and behaviors. AI can enable mass participation and process large quantity of citizens’ input. However,

A Modular Framework for Hybrid Participatory Systems Read More »

Trustworthy AI for human behavior prediction by autonomous vehicles

Julian F. Schumann – TU Delft PhD student For humans to trust autonomous vehicles, they need to have confidence in the vehicles’ ability to reliably resolve space-sharing conflicts with other traffic participants in a safe manner – such as in the case of crossing or merging paths. Planning safe and efficient interactions for autonomous vehicles

Trustworthy AI for human behavior prediction by autonomous vehicles Read More »

Graph Gaussian Processes for Interactive Robot Task Learning

Giovanni Franzese – TU Delft PhD candidate The adaptability of robot manipulators to many different tasks is currently constrained by systematic hard coding of each specific task. Recent machine learning methods like Learning from Demonstrations (LfD) and Reinforcement Learning (RL) have shown promising results in having fast reprogramming of the task using human demonstrations or

Graph Gaussian Processes for Interactive Robot Task Learning Read More »

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

Multi-Objective Statistically Robust Algorithm Ranking Read More »

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

TAILOR Handbook of Trustworthy AI Read More »

Smarter mobility data challenge

As data is at the heart of the industry 4.0, 11 large international groups and the TAILOR network challenge european students from Oct 3 to Dec 3, with the Smarter Mobility Data Challenge for a Greener Future on Codalab. The challenge has been developped by INRIA scientists Marc Schoenaeur and Sebastien Treguer in collaboration with

Smarter mobility data challenge Read More »

Meta Learning from Learning Curves 2

The Meta Learning from Learning Curves challenge is an academic challenge in the 2022 part of the MetaLeran Series of data challenges run by Chalean. a non-for-profit organization lead by Isabelle Guyon (INRIA) in collaboration with TAILOR. The challenge is that of a portfolio of learning algorithms / hyperparameters: it is then possible to run

Meta Learning from Learning Curves 2 Read More »

The TAILOR roadmap shows the path towards Trustworthy AI

The TAILOR project is focussed on Trustworthy Artificial Intelligence through Learning, Optimization and Reasoning, and address topics that are currently very actively investigated. Therefore, defining a roadmap was an ambitious endeavour. The editorial team led by Marc Schoenauer, INRIA, France and Michela Milano, Bologna University have assembled voices from the TAILOR network and beyond to

The TAILOR roadmap shows the path towards Trustworthy AI Read More »