TAILOR - Foundations of Trustworthy AI Integrating Learning Optimisation and Reasoning

From 01-09-2020 to 31-08-2023

Description

The purpose of TAILOR is to build the capacity of providing the scientific foundations for Trustworthy AI in Europe by developing a network of research excellence centres leveraging and combining learning, optimization and reasoning: Throughout this document (starting with its title), learning will mean Machine Learning techniques, starting with the highly successful and today prominent Deep Learning, but also including other approaches like Bayesian Networks, Support Vector Machines, and Decision Trees; optimization will mean continuous, discrete and combinatorial optimization, and their hybrids, and include techniques like convex optimization and gradient methods, constraint programming, heuristics and meta-heuristics, deterministic and stochastic approaches; and reasoning will subsume deductive, inductive, and abductive reasoning, monotonic and non-monotonic reasoning, and include techniques like statistical relational learning, as well as probabilistic and inductive programming.

Team

• Johan Suykens, Co-promoter
• L. De Raedt, Promoter (External)

Financing

Funding: EU Funding - European Funding

Program/Grant Type: EU Other - Other