TAILOR

Publications

volume 12641, 2021

Trustworthy AI - Integrating Learning, Optimization and Reasoning - First International Workshop, TAILOR 2020, Virtual Event, September 4-5, 2020, Revised Selected Papers TAILOR 12641 (2021)

2020

Michele Lombardi, Federico Baldo, Andrea Borghesi, Michela Milano
An Analysis of Regularized Approaches for Constrained Machine Learning. TAILOR (2020)
Alberto Franzin, Thomas Stützle
A Causal Framework for Understanding Optimisation Algorithms. TAILOR (2020)
Pádraig Cunningham, Sarah Jane Delany
Underestimation Bias and Underfitting in Machine Learning. TAILOR (2020)
Roland H. C. Yap
Towards Certifying Trustworthy Machine Learning Systems. TAILOR (2020)
Barteld Braaksma, Piet Daas, Stephan Raaijmakers, Amber Geurts, André Meyer-Vitali
AI-Supported Innovation Monitoring. TAILOR (2020)
Fredrik Präntare, Mattias Tiger, David Bergström, Herman Appelgren, Fredrik Heintz
Towards Utilitarian Combinatorial Assignment with Deep Neural Networks and Heuristic Algorithms. TAILOR (2020)
Farzad Nozarian, Christian Müller, Philipp Slusallek
Uncertainty Quantification and Calibration of Imitation Learning Policy in Autonomous Driving. TAILOR (2020)
Youngmin Kim, Richard Allmendinger, Manuel López-Ibáñez
Safe Learning and Optimization Techniques: Towards a Survey of the State of the Art. TAILOR (2020)
Najlaa Maaroof, Antonio Moreno, Aïda Valls, Mohammed Jabreel
Guided-LORE: Improving LORE with a Focused Search of Neighbours. TAILOR (2020)
Youri Coppens, Denis Steckelmacher, Catholijn M. Jonker, Ann Nowé
Synthesising Reinforcement Learning Policies Through Set-Valued Inductive Rule Learning. TAILOR (2020)
Mohammadreza Amirian, Lukas Tuggener, Ricardo Chavarriaga, Yvan Putra Satyawan, Frank-Peter Schilling, Friedhelm Schwenker, Thilo Stadelmann
Two to Trust: AutoML for Safe Modelling and Interpretable Deep Learning for Robustness. TAILOR (2020)
Stefan Pócos, Iveta Becková, Tomás Kuzma, Igor Farkas
Assessment of Manifold Unfolding in Trained Deep Neural Network Classifiers. TAILOR (2020)
Albert Huizing, Cor J. Veenman, Mark A. Neerincx, Judith Dijk
Hybrid AI: The Way Forward in AI by Developing Four Dimensions. TAILOR (2020)
Yago Fontenla-Seco, Manuel Lama, Alberto Bugarín
Process-To-Text: A Framework for the Quantitative Description of Processes in Natural Language. TAILOR (2020)
José Maria Alonso, Senén Barro, Alberto Bugarín, Kees van Deemter, Claire Gardent, Albert Gatt, Ehud Reiter, Carles Sierra, Mariët Theune, Nava Tintarev, Hitoshi Yano, Katarzyna Budzynska
Interactive Natural Language Technology for Explainable Artificial Intelligence. TAILOR (2020)
Matteo Castiglioni, Diodato Ferraioli, Nicola Gatti, Giulia Landriani
Election Manipulation on Social Networks with Messages on Multiple Candidates Extended Abstract. TAILOR (2020)
Nieves Montes, Carles Sierra
Value-Alignment Equilibrium in Multiagent Systems. TAILOR (2020)
Dimitris Kollias, Y. Vlaxos, M. Seferis, Ilianna Kollia, Levon Sukissian, James Wingate, Stefanos D. Kollias
Transparent Adaptation in Deep Medical Image Diagnosis. TAILOR (2020)
Jesper E. van Engelen, Holger H. Hoos
Semi-supervised Co-ensembling for AutoML. TAILOR (2020)
Miguel Rebollo, C. Carrascosa, Alberto Palomares
Consensus for Collaborative Creation of Risk Maps for COVID-19. TAILOR (2020)
Tomer Libal
Towards Automated GDPR Compliance Checking. TAILOR (2020)
Christel Baier, Maria Christakis, Timo P. Gros, David Groß, Stefan Gumhold, Holger Hermanns, Jörg Hoffmann, Michaela Klauck
Lab Conditions for Research on Explainable Automated Decisions. TAILOR (2020)
Tom Bewley, Jonathan Lawry, Arthur Richards
Modelling Agent Policies with Interpretable Imitation Learning. TAILOR (2020)