Michael Kamp

Publication Activity (10 Years)

Years Active: 2013-2023
Publications (10 Years): 39

Top Venues

CoRR

DSN Workshops

ECML/PKDD (2)

ICDM Workshops

University of Bonn, Germany (PHD)

Education History

University of Bonn, Germany

PHD

Publications

Linara Adilova, Amr Abourayya, Jianning Li, Amin Dada, Henning Petzka, Jan Egger, Jens Kleesiek, Michael Kamp
FAM: Relative Flatness Aware Minimization. CoRR (2023)
Jianning Li, André Ferreira, Behrus Puladi, Victor Alves, Michael Kamp, Moon S. Kim, Felix Nensa, Jens Kleesiek, Seyed-Ahmad Ahmadi, Jan Egger
Open-source skull reconstruction with MONAI. SoftwareX 23 (2023)
Frederic Jonske, Moon S. Kim, Enrico Nasca, Janis Evers, Johannes Haubold, René Hosch, Felix Nensa, Michael Kamp, Constantin Seibold, Jan Egger, Jens Kleesiek
Why does my medical AI look at pictures of birds? Exploring the efficacy of transfer learning across domain boundaries. CoRR (2023)
Amr Abourayya, Jens Kleesiek, Kanishka Rao, Erman Ayday, Bharat Rao, Geoff Webb, Michael Kamp
Protecting Sensitive Data through Federated Co-Training. CoRR (2023)
Michael Kamp, Jonas Fischer, Jilles Vreeken
Federated Learning from Small Datasets. ICLR (2023)
Osman Mian, Michael Kamp, Jilles Vreeken
Information-Theoretic Causal Discovery and Intervention Detection over Multiple Environments. AAAI (2023)
Linara Adilova, Amr Abourayya, Jianning Li, Amin Dada, Henning Petzka, Jan Egger, Jens Kleesiek, Michael Kamp
FAM: Relative Flatness Aware Minimization. TAG-ML (2023)
Osman Ali Mian, David Kaltenpoth, Michael Kamp, Jilles Vreeken
Nothing but Regrets - Privacy-Preserving Federated Causal Discovery. AISTATS (2023)
Junhong Wang, Yun Li, Zhaoyu Zhou, Chengshun Wang, Yijie Hou, Li Zhang, Xiangyang Xue, Michael Kamp, Xiaolong Luke Zhang, Siming Chen
When, Where and How Does it Fail? A Spatial-Temporal Visual Analytics Approach for Interpretable Object Detection in Autonomous Driving. IEEE Trans. Vis. Comput. Graph. 29 (12) (2023)
Osman Mian, David Kaltenpoth, Michael Kamp
Regret-based Federated Causal Discovery. CD@KDD (2022)
Jianning Li, André Ferreira, Behrus Puladi, Victor Alves, Michael Kamp, Moon-Sung Kim, Felix Nensa, Jens Kleesiek, Seyed-Ahmad Ahmadi, Jan Egger
Open-Source Skull Reconstruction with MONAI. CoRR (2022)
Linara Adilova, Siming Chen, Michael Kamp
Novelty Detection in Sequential Data by Informed Clustering and Modeling. CoRR (2021)
Xiaoxiao Li, Meirui Jiang, Xiaofei Zhang, Michael Kamp, Qi Dou
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization. CoRR (2021)
Florian Linsner, Linara Adilova, Sina Däubener, Michael Kamp, Asja Fischer
Approaches to Uncertainty Quantification in Federated Deep Learning. PKDD/ECML Workshops (1) (2021)
Meirui Jiang, Xiaofei Zhang, Michael Kamp, Xiaoxiao Li, Qi Dou
TsmoBN: Interventional Generalization for Unseen Clients in Federated Learning. CoRR (2021)
Ibéria Medeiros, Ilir Gashi, Michael Kamp, Pedro Ferreira
Third International Workshop on Data-Centric Dependability and Security (DCDS). DSN Workshops (2021)
Xiaoxiao Li, Meirui Jiang, Xiaofei Zhang, Michael Kamp, Qi Dou
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization. ICLR (2021)
Michael Kamp, Jonas Fischer, Jilles Vreeken
Federated Learning from Small Datasets. CoRR (2021)
Henning Petzka, Michael Kamp, Linara Adilova, Cristian Sminchisescu, Mario Boley
Relative Flatness and Generalization. NeurIPS (2021)
Lukas Heppe, Michael Kamp, Linara Adilova, Danny Heinrich, Nico Piatkowski, Katharina Morik
Resource-Constrained On-Device Learning by Dynamic Averaging. PKDD/ECML Workshops (2020)
Pascal Welke, Florian Seiffarth, Michael Kamp, Stefan Wrobel
HOPS: Probabilistic Subtree Mining for Small and Large Graphs. KDD (2020)
Lukas Heppe, Michael Kamp, Linara Adilova, Danny Heinrich, Nico Piatkowski, Katharina Morik
Resource-Constrained On-Device Learning by Dynamic Averaging. CoRR (2020)
Henning Petzka, Linara Adilova, Michael Kamp, Cristian Sminchisescu
Feature-Robustness, Flatness and Generalization Error for Deep Neural Networks. CoRR (2020)
Ibéria Medeiros, Ilir Gashi, Michael Kamp, Pedro Ferreira
Second International Workshop on Data-Centric Dependability and Security (DCDS). DSN Workshops (2020)
Michael Kamp, Mario Boley, Michael Mock, Daniel Keren, Assaf Schuster, Izchak Sharfman
Adaptive Communication Bounds for Distributed Online Learning. CoRR (2019)
Linara Adilova, Livin Natious, Siming Chen, Olivier Thonnard, Michael Kamp
System Misuse Detection Via Informed Behavior Clustering and Modeling. DSN Workshops (2019)
Linara Adilova, Julia Rosenzweig, Michael Kamp
Information-Theoretic Perspective of Federated Learning. CoRR (2019)
Linara Adilova, Livin Natious, Siming Chen, Olivier Thonnard, Michael Kamp
System Misuse Detection via Informed Behavior Clustering and Modeling. CoRR (2019)
Michael Kamp, Sebastian Bothe, Mario Boley, Michael Mock
Communication-Efficient Distributed Online Learning with Kernels. CoRR (2019)
Henning Petzka, Linara Adilova, Michael Kamp, Cristian Sminchisescu
A Reparameterization-Invariant Flatness Measure for Deep Neural Networks. CoRR (2019)
Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel
Efficient Decentralized Deep Learning by Dynamic Model Averaging. CoRR (2018)
Sven Giesselbach, Katrin Ullrich, Michael Kamp, Daniel Paurat, Thomas Gärtner
Corresponding Projections for Orphan Screening. CoRR (2018)
Michael Kamp, Mario Boley, Olana Missura, Thomas Gärtner
Effective Parallelisation for Machine Learning. CoRR (2018)
Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel
Efficient Decentralized Deep Learning by Dynamic Model Averaging. ECML/PKDD (1) (2018)
Katrin Ullrich, Michael Kamp, Thomas Gärtner, Martin Vogt, Stefan Wrobel
Co-Regularised Support Vector Regression. ECML/PKDD (2) (2017)
Michael Kamp, Mario Boley, Olana Missura, Thomas Gärtner
Effective Parallelisation for Machine Learning. NIPS (2017)
Ioannis Flouris, Nikos Giatrakos, Antonios Deligiannakis, Minos N. Garofalakis, Michael Kamp, Michael Mock
Issues in complex event processing: Status and prospects in the Big Data era. J. Syst. Softw. 127 (2017)
Katrin Ullrich, Michael Kamp, Thomas Gärtner, Martin Vogt, Stefan Wrobel
Ligand-Based Virtual Screening with Co-regularised Support Vector Regression. ICDM Workshops (2016)
Michael Kamp, Sebastian Bothe, Mario Boley, Michael Mock
Communication-Efficient Distributed Online Learning with Kernels. ECML/PKDD (2) (2016)
Michael Kamp, Mario Boley, Thomas Gärtner
Beating Human Analysts in Nowcasting Corporate Earnings by using Publicly Available Stock Price and Correlation Features. SDM (2014)
Michael Kamp, Mario Boley, Daniel Keren, Assaf Schuster, Izchak Sharfman
Communication-Efficient Distributed Online Prediction by Dynamic Model Synchronization. ECML/PKDD (1) (2014)
Mario Boley, Michael Kamp, Daniel Keren, Assaf Schuster, Izchak Sharfman
Communication-Efficient Distributed Online Prediction using Dynamic Model Synchronizations. BD3@VLDB (2013)
Michael Kamp, Mario Boley, Thomas Gärtner
Beating Human Analysts in Nowcasting Corporate Earnings by Using Publicly Available Stock Price and Correlation Features. ICDM Workshops (2013)
Michael Kamp, Christine Kopp, Michael Mock, Mario Boley, Michael May
Privacy-Preserving Mobility Monitoring Using Sketches of Stationary Sensor Readings. ECML/PKDD (3) (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Michael Kamp