2 citations · 2 across the 2 of their papers we have counts for
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cs.LG2021
Prior-Independent Auctions for the Demand Side of Federated Learning
Andreas Haupt, Vaikkunth Mugunthan
Federated learning (FL) is a paradigm that allows distributed clients to learn a shared machine learning model without sharing their sensitive training data. While largely decentra…
cs.LG2017★ 2 cited
Classification on Large Networks: A Quantitative Bound via Motifs and Graphons
Andreas Haupt, Mohammad Khatami, Thomas Schultz +1
When each data point is a large graph, graph statistics such as densities of certain subgraphs (motifs) can be used as feature vectors for machine learning. While intuitive, motif…