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Applying Interdisciplinary Frameworks to Understand Algorithmic Decision-Making


May 26, 2023
Timothée Schmude, Laura Koesten, Torsten Möller, Sebastian Tschiatschek

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* 5 pages, 1 figure 

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Learning Safety Constraints from Demonstrations with Unknown Rewards


May 25, 2023
David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause

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Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes


Mar 28, 2023
Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, Adish Singla

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* Preprint. Accepted as a paper at the AIED'22 conference 

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Interactively Learning Preference Constraints in Linear Bandits


Jun 10, 2022
David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause

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* Accepted to International Conference on Machine Learning (ICML), 2022 

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Equity and Fairness of Bayesian Knowledge Tracing


May 04, 2022
Sebastian Tschiatschek, Maria Knobelsdorf, Adish Singla

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MDP Abstraction with Successor Features


Oct 18, 2021
Dongge Han, Michael Wooldridge, Sebastian Tschiatschek

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Contextual HyperNetworks for Novel Feature Adaptation


Apr 12, 2021
Angus Lamb, Evgeny Saveliev, Yingzhen Li, Sebastian Tschiatschek, Camilla Longden, Simon Woodhead, José Miguel Hernández-Lobato, Richard E. Turner, Pashmina Cameron, Cheng Zhang

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* 17 pages, 9 Figures, workshop paper at NeurIPS 2020 Meta-Learning Workshop 

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Information Directed Reward Learning for Reinforcement Learning


Feb 24, 2021
David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause

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Reinforcement Learning with Efficient Active Feature Acquisition


Nov 02, 2020
Haiyan Yin, Yingzhen Li, Sinno Jialin Pan, Cheng Zhang, Sebastian Tschiatschek

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Replication-Robust Payoff-Allocation with Applications in Machine Learning Marketplaces


Jun 25, 2020
Dongge Han, Shruti Tople, Alex Rogers, Michael Wooldridge, Olga Ohrimenko, Sebastian Tschiatschek

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