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MANDERA: Malicious Node Detection in Federated Learning via Ranking
Although we know that the benign gradients and Byzantine attacked gradients are distributed differently, to detect the malicious gradients is challenging due to (1) the gradient is high-dimensional and each dimension has its unique distribution and (2) the benign gradients and the attacked gradients are always mixed (two-sample test methods cannot apply directly).
Stein Variational Gradient Descent for Approximate Bayesian Computation
Approximate Bayesian Computation (ABC) provides a generic framework of Bayesian inference for likelihood-free models, but sampling based posterior approximation is often time-consuming and has difficulty accessing the convergence.
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