Michael Kamp

According to our database, Michael Kamp authored at least 41 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Federated Binary Matrix Factorization using Proximal Optimization.

Sebastian Dalleiger, Jilles Vreeken, Michael Kamp

CoRR, 2024

Landscaping Linear Mode Connectivity.

Sidak Pal Singh, Linara Adilova, Michael Kamp, Asja Fischer, Bernhard Schölkopf, Thomas Hofmann

CoRR, 2024

The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective.

Nils Philipp Walter, Linara Adilova, Jilles Vreeken, Michael Kamp

CoRR, 2024

Visual Computing for Autonomous Driving.

Siming Chen, Liang Gou, Michael Kamp, Dong Sun

IEEE Computer Graphics and Applications, 2024

Layer-wise linear mode connectivity.

Linara Adilova, Maksym Andriushchenko, Michael Kamp, Asja Fischer, Martin Jaggi

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Orthogonal Gradient Boosting for Simpler Additive Rule Ensembles.

Fan Yang, Pierre Le Bodic, Michael Kamp, Mario Boley

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

When, Where and How Does it Fail? A Spatial-Temporal Visual Analytics Approach for Interpretable Object Detection in Autonomous Driving.

Junhong Wang, Yun Li, Zhaoyu Zhou, Chengshun Wang, Yijie Hou, Li Zhang, Xiangyang Xue, Michael Kamp, Xiaolong Luke Zhang, Siming Chen

IEEE Trans. Vis. Comput. Graph., December, 2023

Open-source skull reconstruction with MONAI.

Jianning Li, André Ferreira, Behrus Puladi, Victor Alves, Michael Kamp, Moon S. Kim, Felix Nensa, Jens Kleesiek, Seyed-Ahmad Ahmadi, Jan Egger

SoftwareX, July, 2023

Protecting Sensitive Data through Federated Co-Training.

Amr Abourayya, Jens Kleesiek, Kanishka Rao, Erman Ayday, Bharat Rao, Geoffrey I. Webb, Michael Kamp

CoRR, 2023

Why does my medical AI look at pictures of birds? Exploring the efficacy of transfer learning across domain boundaries.

Frederic Jonske, Moon S. Kim, Enrico Nasca, Janis Evers, Johannes Haubold, René Hosch, Felix Nensa, Michael Kamp, Constantin Seibold, Jan Egger, Jens Kleesiek

CoRR, 2023

FAM: Relative Flatness Aware Minimization.

Linara Adilova, Amr Abourayya, Jianning Li, Amin Dada, Henning Petzka, Jan Egger, Jens Kleesiek, Michael Kamp

Proceedings of the Topological, 2023

Federated Learning from Small Datasets.

Michael Kamp, Jonas Fischer, Jilles Vreeken

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Nothing but Regrets - Privacy-Preserving Federated Causal Discovery.

Osman Mian, David Kaltenpoth, Michael Kamp, Jilles Vreeken

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Information-Theoretic Causal Discovery and Intervention Detection over Multiple Environments.

Osman Mian, Michael Kamp, Jilles Vreeken

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Regret-based Federated Causal Discovery.

Osman Mian, David Kaltenpoth, Michael Kamp

Proceedings of the KDD'22 Workshop on Causal Discovery, 15 August 2022, Washington DC, USA, 2022

2021

TsmoBN: Interventional Generalization for Unseen Clients in Federated Learning.

Meirui Jiang, Xiaofei Zhang, Michael Kamp, Xiaoxiao Li, Qi Dou

CoRR, 2021

Novelty Detection in Sequential Data by Informed Clustering and Modeling.

Linara Adilova, Siming Chen, Michael Kamp

CoRR, 2021

Approaches to Uncertainty Quantification in Federated Deep Learning.

Florian Linsner, Linara Adilova, Sina Däubener, Michael Kamp, Asja Fischer

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

Relative Flatness and Generalization.

Henning Petzka, Michael Kamp, Linara Adilova, Cristian Sminchisescu, Mario Boley

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

FedBN: Federated Learning on Non-IID Features via Local Batch Normalization.

Xiaoxiao Li, Meirui Jiang, Xiaofei Zhang, Michael Kamp, Qi Dou

Proceedings of the 9th International Conference on Learning Representations, 2021

Third International Workshop on Data-Centric Dependability and Security (DCDS).

Ibéria Medeiros, Ilir Gashi, Michael Kamp, Pedro Ferreira

Proceedings of the 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, 2021

2020

Feature-Robustness, Flatness and Generalization Error for Deep Neural Networks.

Henning Petzka, Linara Adilova, Michael Kamp, Cristian Sminchisescu

CoRR, 2020

Resource-Constrained On-Device Learning by Dynamic Averaging.

Lukas Heppe, Michael Kamp, Linara Adilova, Danny Heinrich, Nico Piatkowski, Katharina Morik

Proceedings of the ECML PKDD 2020 Workshops, 2020

HOPS: Probabilistic Subtree Mining for Small and Large Graphs.

Pascal Welke, Florian Seiffarth, Michael Kamp, Stefan Wrobel

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Second International Workshop on Data-Centric Dependability and Security (DCDS).

Ibéria Medeiros, Ilir Gashi, Michael Kamp, Pedro Ferreira

Proceedings of the 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, 2020

2019

Black-Box Parallelization for Machine Learning.

Michael Kamp

PhD thesis, 2019

A Reparameterization-Invariant Flatness Measure for Deep Neural Networks.

Henning Petzka, Linara Adilova, Michael Kamp, Cristian Sminchisescu

CoRR, 2019

Adaptive Communication Bounds for Distributed Online Learning.

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

CoRR, 2019

Information-Theoretic Perspective of Federated Learning.

Linara Adilova, Julia Rosenzweig, Michael Kamp

CoRR, 2019

System Misuse Detection Via Informed Behavior Clustering and Modeling.

Linara Adilova, Livin Natious, Siming Chen, Olivier Thonnard, Michael Kamp

Proceedings of the 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, 2019

2018

Corresponding Projections for Orphan Screening.

Sven Giesselbach, Katrin Ullrich, Michael Kamp, Daniel Paurat, Thomas Gärtner

CoRR, 2018

Efficient Decentralized Deep Learning by Dynamic Model Averaging.

Michael Kamp, Linara Adilova, Joachim Sicking, Fabian Hüger, Peter Schlicht, Tim Wirtz, Stefan Wrobel

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

2017

Issues in complex event processing: Status and prospects in the Big Data era.

Ioannis Flouris, Nikos Giatrakos, Antonios Deligiannakis, Minos N. Garofalakis, Michael Kamp, Michael Mock

J. Syst. Softw., 2017

Co-Regularised Support Vector Regression.

Katrin Ullrich, Michael Kamp, Thomas Gärtner, Martin Vogt, Stefan Wrobel

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Effective Parallelisation for Machine Learning.

Michael Kamp, Mario Boley, Olana Missura, Thomas Gärtner

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Communication-Efficient Distributed Online Learning with Kernels.

Michael Kamp, Sebastian Bothe, Mario Boley, Michael Mock

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Ligand-Based Virtual Screening with Co-regularised Support Vector Regression.

Katrin Ullrich, Michael Kamp, Thomas Gärtner, Martin Vogt, Stefan Wrobel

Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

2014

Communication-Efficient Distributed Online Prediction by Dynamic Model Synchronization.

Michael Kamp, Mario Boley, Daniel Keren, Assaf Schuster, Izchak Sharfman

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

2013

Communication-Efficient Distributed Online Prediction using Dynamic Model Synchronizations.

Mario Boley, Michael Kamp, Daniel Keren, Assaf Schuster, Izchak Sharfman

Proceedings of the First International Workshop on Big Dynamic Distributed Data, 2013

Privacy-Preserving Mobility Monitoring Using Sketches of Stationary Sensor Readings.

Michael Kamp, Christine Kopp, Michael Mock, Mario Boley, Michael May

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Beating Human Analysts in Nowcasting Corporate Earnings by Using Publicly Available Stock Price and Correlation Features.

Michael Kamp, Mario Boley, Thomas Gärtner

Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013