Fractional Hedonic Games: Individual and Group Stability. - Florian Brandl; Felix Brandt 001; Martin Strobel 001 (AAMAS, 2015)

Analyzing the Practical Relevance of Voting Paradoxes via Ehrhart Theory, Computer Simulations, and Empirical Data. - Felix Brandt 001; Christian Geist; Martin Strobel 001 (AAMAS, 2016)

A Characterization of Monotone Influence Measures for Data Classification. - Jakub Sliwinski; Martin Strobel 001; Yair Zick (CoRR, 2017)

Catching Captain Jack: Efficient Time and Space Dependent Patrols to Combat Oil-Siphoning in International Waters. - Xinrun Wang; Bo An 001; Martin Strobel 001; Fookwai Kong (AAAI, 2018)

An Axiomatic Approach to Explain Computer Generated Decisions: Extended Abstract. - Martin Strobel 001 (AIES, 2018)

An Axiomatic Approach to Linear Explanations in Data Classification. - Jakub Sliwinski; Martin Strobel 001; Yair Zick (IUI Workshops, 2018)

Axiomatic Characterization of Data-Driven Influence Measures for Classification. - Jakub Sliwinski; Martin Strobel 001; Yair Zick (AAAI, 2019)

Exploring the No-Show Paradox for Condorcet Extensions Using Ehrhart Theory and Computer Simulations. - Felix Brandt 001; Johannes Hofbauer; Martin Strobel 001 (AAMAS, 2019)

Aspects of Transparency in Machine Learning. - Martin Strobel 001 (AAMAS, 2019)

Privacy Risks of Explaining Machine Learning Models. - Reza Shokri; Martin Strobel 001; Yair Zick (CoRR, 2019)

On the Privacy Risks of Model Explanations. - Reza Shokri; Martin Strobel 001; Yair Zick (AIES, 2021)

High Dimensional Model Explanations: An Axiomatic Approach. - Neel Patel; Martin Strobel 001; Yair Zick (FAccT, 2021)

Data Privacy and Trustworthy Machine Learning. - Martin Strobel 001; Reza Shokri (IEEE Secur. Priv., 2022)

On The Impact of Machine Learning Randomness on Group Fairness. - Prakhar Ganesh; Hongyan Chang; Martin Strobel 001; Reza Shokri (FAccT, 2023)

Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play. - Jeremiah Zhe Liu; Krishnamurthy (Dj) Dvijotham; Jihyeon Lee; Quan Yuan 001; Martin Strobel 001; Balaji Lakshminarayanan; Deepak Ramachandran (CoRR, 2023)

Towards Regulatable AI Systems: Technical Gaps and Policy Opportunities. - Xudong Shen; Hannah Brown; Jiashu Tao; Martin Strobel 001; Yao Tong; Akshay Narayan 002; Harold Soh; Finale Doshi-Velez (CoRR, 2023)

Directions of Technical Innovation for Regulatable AI Systems. - Xudong Shen; Hannah Brown; Jiashu Tao; Martin Strobel 001; Yao Tong; Akshay Narayan 002; Harold Soh; Finale Doshi-Velez (Commun. ACM, 2024)