7 citations · 18 across the 9 of their papers we have counts for
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cs.LG2024★ 1 cited
Differentially Private Distributed Inference for Multicenter Clinical Studies
Marios Papachristou, M. Amin Rahimian
Extracting reliable conclusions from data distributed across institutions is a core problem in healthcare: pooling patient records would improve inference, but privacy regulations…
cs.LG2023★ 4 cited
Differentially Private Distributed Estimation and Learning
Marios Papachristou, M. Amin Rahimian
We study distributed estimation and learning problems in a networked environment where agents exchange information to estimate unknown statistical properties of random variables fr…
cs.LG2022★ 1 cited
GLINKX: A Scalable Unified Framework For Homophilous and Heterophilous Graphs
Marios Papachristou, Rishab Goel, Frank Portman +2
In graph learning, there have been two predominant inductive biases regarding graph-inspired architectures: On the one hand, higher-order interactions and message passing work well…