20 citations · 70 across the 24 of their papers we have counts for
5 papers · 1 filter
Sequential Monte Carlo Sampling of Feasible Regions Represented by R-Functions
Sinan Yıldırım, Sergei Kucherenko
Feasible-region sampling and volume estimation become increasingly inefficient when constraints define only a small fraction of a convenient bounding domain. We combine R-functions…
Combining Homomorphic Encryption and Differential Privacy in Federated Learning for Model Inspection and Availability
Ceren Yıldırım, Kamer Kaya, Sinan Yıldırım +1
The increasing prevalence of decentralized data has led to a growing interest in federated learning, which enables collaborative model training without clients sharing their sensit…
The Quick and the Dead: Estimating Sparse-Matrix Permanents with Adaptive Work Filtering
Deniz Elbek, Yiğit Manafi, Zeynep Gürdal +2
Rasmussen's permanent estimator is a simple and unbiased estimator for the permanent of a binary matrix, but its practical performance can be limited by trajectories that terminate…
Bayesian Membership Privacy for Graph Neural Networks
Sinan Yıldırım, Megha Khosla
Existing privacy analyses for Graph Neural Networks (GNNs) largely inherit assumptions from non-graph settings, overlooking structural correlations and stochastic training-graph sa…
Multiple Jump MCMC: A Scalable Algorithm for Bayesian Inference on Binary Model Spaces
Lucas Vogels, Reza Mohammadi, Marit Schoonhoven +2
This article considers Bayesian model inference on binary model spaces. Binary model spaces are used by a large class of models, including graphical models, variable selection, mix…