Martin Strobel

21 papers A* 3A 4C 2Journal 9Unranked 3
YearRankTypeTitle / Venue / Authors
2026 A* conf
Understanding the Effects of GenAI as No-Code Alternative for Teaching Machine Learning Workflows.
AAAI
Martin Strobel
2024 J jnl
Directions of Technical Innovation for Regulatable AI Systems.
Commun. ACM
Xudong Shen, Hannah Brown, Jiashu Tao, Martin Strobel, Yao Tong, Akshay Narayan, Harold Soh, Finale Doshi-Velez
2023 — conf
On The Impact of Machine Learning Randomness on Group Fairness.
FAccT
Prakhar Ganesh, Hongyan Chang, Martin Strobel, Reza Shokri
2023 J jnl
On The Impact of Machine Learning Randomness on Group Fairness.
CoRR
Prakhar Ganesh, Hongyan Chang, Martin Strobel, Reza Shokri
2023 J jnl
Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play.
CoRR
Jeremiah Zhe Liu, Krishnamurthy (Dj) Dvijotham, Jihyeon Lee, Quan Yuan, Martin Strobel, Balaji Lakshminarayanan, Deepak Ramachandran
2023 J jnl
Towards Regulatable AI Systems: Technical Gaps and Policy Opportunities.
CoRR
Xudong Shen, Hannah Brown, Jiashu Tao, Martin Strobel, Yao Tong, Akshay Narayan, Harold Soh, Finale Doshi-Velez
2022 J jnl
Data Privacy and Trustworthy Machine Learning.
CoRR
Martin Strobel, Reza Shokri
2022 J jnl
Data Privacy and Trustworthy Machine Learning.
IEEE Secur. Priv.
Martin Strobel, Reza Shokri
2021 — conf
High Dimensional Model Explanations: An Axiomatic Approach.
FAccT
Neel Patel, Martin Strobel, Yair Zick
2021 C conf
On the Privacy Risks of Model Explanations.
AIES
Reza Shokri, Martin Strobel, Yair Zick
2020 J jnl
High Dimensional Model Explanations: an Axiomatic Approach.
CoRR
Neel Patel, Martin Strobel, Yair Zick
2019 A conf
Aspects of Transparency in Machine Learning.
AAMAS
Martin Strobel
2019 A* conf
Axiomatic Characterization of Data-Driven Influence Measures for Classification.
AAAI
Jakub Sliwinski, Martin Strobel, Yair Zick
2019 A conf
Exploring the No-Show Paradox for Condorcet Extensions Using Ehrhart Theory and Computer Simulations.
AAMAS
Felix Brandt, Johannes Hofbauer, Martin Strobel
2019 J jnl
Privacy Risks of Explaining Machine Learning Models.
CoRR
Reza Shokri, Martin Strobel, Yair Zick
2018 C conf
An Axiomatic Approach to Explain Computer Generated Decisions: Extended Abstract.
AIES
Martin Strobel
2018 — conf
An Axiomatic Approach to Linear Explanations in Data Classification.
IUI Workshops
Jakub Sliwinski, Martin Strobel, Yair Zick
2018 A* conf
Catching Captain Jack: Efficient Time and Space Dependent Patrols to Combat Oil-Siphoning in International Waters.
AAAI
Xinrun Wang, Bo An, Martin Strobel, Fookwai Kong
2017 J jnl
A Characterization of Monotone Influence Measures for Data Classification.
CoRR
Jakub Sliwinski, Martin Strobel, Yair Zick
2016 A conf
Analyzing the Practical Relevance of Voting Paradoxes via Ehrhart Theory, Computer Simulations, and Empirical Data.
AAMAS
Felix Brandt, Christian Geist, Martin Strobel
2015 A conf
Fractional Hedonic Games: Individual and Group Stability.
AAMAS
Florian Brandl, Felix Brandt, Martin Strobel