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 »
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 »
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 »
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 »
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 »
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 »
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 »
On 13th and 14th of September, TAILOR had its second annual conference. This time the conference was hosted in Prague, at the beautiful location of Charles University. The major objectives of the conference was to discuss about what TAILOR did so far, to make a plan for the next year, and finally to meet in
Impressions from TAILOR Conference in Prague Read More »
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 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 »
