3 papers
math.OC2025
DIGing--SGLD: Decentralized and Scalable Langevin Sampling over Time--Varying Networks
Waheed U. Bajwa, Mert Gurbuzbalaban, Mustafa Ali Kutbay +2
Sampling from a target distribution induced by training data is central to Bayesian learning, with Stochastic Gradient Langevin Dynamics (SGLD) serving as a key tool for scalable p…
cs.LG2025
RESIST: Resilient Decentralized Learning Using Consensus Gradient Descent
Cheng Fang, Rishabh Dixit, Waheed U. Bajwa +2
Empirical risk minimization (ERM) is a cornerstone of modern machine learning. This paper focuses on the man-in-the-middle (MITM) attack, wherein adversaries exploit communication…
cs.LG2024
Mitigating Data Injection Attacks on Federated Learning
Or Shalom, Amir Leshem, Waheed U. Bajwa
Federated learning is a technique that allows multiple entities to collaboratively train models using their data without compromising data privacy. However, despite its advantages,…