39 citations · 87 across the 4 of their papers we have counts for
4 papers
Diffusion-Based Surrogate Modeling and Multi-Fidelity Calibration
Naichen Shi, Hao Yan, Shenghan Guo +1
Physics simulations have become fundamental tools to study myriad engineering systems. As physics simulations often involve simplifications, their outputs should be calibrated usin…
Collaborative and Distributed Bayesian Optimization via Consensus: Showcasing the Power of Collaboration for Optimal Design
Xubo Yue, Raed Al Kontar, Albert S. Berahas +2
Optimal design is a critical yet challenging task within many applications. This challenge arises from the need for extensive trial and error, often done through simulations or run…
GIFAIR-FL: A Framework for Group and Individual Fairness in Federated Learning
Xubo Yue, Maher Nouiehed, Raed Al Kontar
In this paper we propose \texttt{GIFAIR-FL}: a framework that imposes \textbf{G}roup and \textbf{I}ndividual \textbf{FAIR}ness to \textbf{F}ederated \textbf{L}earning settings. By…
Fed-ensemble: Improving Generalization through Model Ensembling in Federated Learning
Naichen Shi, Fan Lai, Raed Al Kontar +1
In this paper we propose Fed-ensemble: a simple approach that bringsmodel ensembling to federated learning (FL). Instead of aggregating localmodels to update a single global model,…