Michael Mock

Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety

Apr 29, 2021
Sebastian Houben, Stephanie Abrecht, Maram Akila, Andreas Bär, Felix Brockherde, Patrick Feifel, Tim Fingscheidt, Sujan Sai Gannamaneni, Seyed Eghbal Ghobadi, Ahmed Hammam, Anselm Haselhoff, Felix Hauser, Christian Heinzemann, Marco Hoffmann, Nikhil Kapoor, Falk Kappel, Marvin Klingner, Jan Kronenberger, Fabian Küppers, Jonas Löhdefink, Michael Mlynarski, Michael Mock, Firas Mualla, Svetlana Pavlitskaya, Maximilian Poretschkin, Alexander Pohl, Varun Ravi-Kumar, Julia Rosenzweig, Matthias Rottmann, Stefan Rüping, Timo Sämann, Jan David Schneider, Elena Schulz, Gesina Schwalbe, Joachim Sicking, Toshika Srivastava, Serin Varghese, Michael Weber, Sebastian Wirkert, Tim Wirtz, Matthias Woehrle

* 94 pages

Access Paper or Ask Questions

Patch Shortcuts: Interpretable Proxy Models Efficiently Find Black-Box Vulnerabilities

Apr 22, 2021
Julia Rosenzweig, Joachim Sicking, Sebastian Houben, Michael Mock, Maram Akila

Figure 2 for Patch Shortcuts: Interpretable Proxy Models Efficiently Find Black-Box Vulnerabilities

Figure 3 for Patch Shortcuts: Interpretable Proxy Models Efficiently Find Black-Box Vulnerabilities

Figure 4 for Patch Shortcuts: Interpretable Proxy Models Efficiently Find Black-Box Vulnerabilities

* Under IEEE Copyright; accepted at the SAIAD (Safe Artificial Intelligence for Automated Driving) Workshop at CVPR 2021

Access Paper or Ask Questions

Communication-Efficient Distributed Online Learning with Kernels

Nov 28, 2019
Michael Kamp, Sebastian Bothe, Mario Boley, Michael Mock

Figure 2 for Communication-Efficient Distributed Online Learning with Kernels

* Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2016

Access Paper or Ask Questions

Adaptive Communication Bounds for Distributed Online Learning

Nov 28, 2019
Michael Kamp, Mario Boley, Michael Mock, Daniel Keren, Assaf Schuster, Izchak Sharfman

* Proceedings of the 7th NIPS Workshop on Optimization for Machine Learning, 2014

Access Paper or Ask Questions