Convergence of Byzantine-Resilient Gradient Tracking via Probabilistic Edge Dropout
Convergence of Byzantine-Resilient Gradient Tracking via Probabilistic Edge Dropout explores A novel stochastic gradient tracking method designed to maintain convergence properties in distributed optimization networks with Byzantine agents.. Commercial viability score: 3/10 in Distributed Optimization.
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