2 citations · 3 across the 4 of their papers we have counts for
5 papers
A Reparameterization-Invariant Flatness Measure for Deep Neural Networks
Henning Petzka, Linara Adilova, Michael Kamp +1
The performance of deep neural networks is often attributed to their automated, task-related feature construction. It remains an open question, though, why this leads to solutions…
Communication-Efficient Distributed Online Learning with Kernels
Michael Kamp, Sebastian Bothe, Mario Boley +1
We propose an efficient distributed online learning protocol for low-latency real-time services. It extends a previously presented protocol to kernelized online learners that repre…
Adaptive Communication Bounds for Distributed Online Learning
Michael Kamp, Mario Boley, Michael Mock +3
We consider distributed online learning protocols that control the exchange of information between local learners in a round-based learning scenario. The learning performance of su…
Information-Theoretic Perspective of Federated Learning
Linara Adilova, Julia Rosenzweig, Michael Kamp
An approach to distributed machine learning is to train models on local datasets and aggregate these models into a single, stronger model. A popular instance of this form of parall…
System Misuse Detection via Informed Behavior Clustering and Modeling
Linara Adilova, Livin Natious, Siming Chen +2
One of the main tasks of cybersecurity is recognizing malicious interactions with an arbitrary system. Currently, the logging information from each interaction can be collected in…