A min-rule distributed learning algorithm for hypothesis testing achieves network-independent exponential convergence rates and Byzantine resilience, outperforming belief-averaging methods.
Resilient consensus of second-order agent networks: Asynchronous update rules with delays,
3 Pith papers cite this work. Polarity classification is still indexing.
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Presents methods for resilient leader-follower consensus to arbitrary reference values in time-varying graphs with discrete-time dynamics despite bounded adversarial agents.
A resilient leader-follower consensus method for discrete-time systems that enables tracking of time-varying references outside the initial convex hull despite bounded adversarial agents.
citing papers explorer
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A New Approach to Distributed Hypothesis Testing and Non-Bayesian Learning: Improved Learning Rate and Byzantine-Resilience
A min-rule distributed learning algorithm for hypothesis testing achieves network-independent exponential convergence rates and Byzantine resilience, outperforming belief-averaging methods.
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Resilient Leader-Follower Consensus to Arbitrary Reference Values in Time-Varying Graphs
Presents methods for resilient leader-follower consensus to arbitrary reference values in time-varying graphs with discrete-time dynamics despite bounded adversarial agents.
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Resilient Leader-Follower Consensus with Time-Varying Leaders in Discrete-Time Systems
A resilient leader-follower consensus method for discrete-time systems that enables tracking of time-varying references outside the initial convex hull despite bounded adversarial agents.