Author Archives: Ruben Mayer

Our paper titled “How Reliable Are Streams? End-to-End Processing-Guarantee Validation and Performance Benchmarking of Stream Processing Systems” has just been accepted for VLDB 2025!

Two papers on GNN and Federated Learning systems have been accepted at international top conferences: Nikolai Merkel, Pierre Toussing, Ruben Mayer, and Hans-Arno Jacobsen. “Can Graph Reordering Speed Up Graph Neural Network Training? An Experimental Study.” 15 Pages. Accepted at VLDB 2025. Preprint available: https://arxiv.org/abs/2409.11129 Herbert Woisetschläger, Alexander Erben, Ruben Mayer, Shiqiang Wang, and Hans-ArnoContinue reading “Papers accepted at VLDB and Middleware conference”

Our paper titled “An Experimental Comparison of Partitioning Strategies for Distributed Graph Neural Network Training” has been accepted at EDBT 2025! A preprint can be found on Arxiv: https://arxiv.org/abs/2308.15602

Two machine learning papers have been accepted: Herbert Woisetschläger, Alexander Erben, Shiqiang Wang, Ruben Mayer, and Hans-Arno Jacobsen. “A Survey on Efficient Federated Learning Methods for Foundation Model Training.” In Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI ’24). Preprint: https://arxiv.org/abs/2401.04472 Herbert Woisetschläger, Alexander Erben, Shiqiang Wang, Ruben Mayer, and Hans-Arno Jacobsen.Continue reading “Papers at IJCAI and DEEM”