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Asynchronous trajectory estimation can slash communication needs by nearly 97% while boosting accuracy in multi-robot systems.
Existing differential privacy methods struggle with symbolic trajectory data, but this new mechanism slashes error by up to 55% on real-world data.
Achieve differentially private Markov chain modeling with minimal impact on accuracy, showing less than 2% error in the stationary distribution under typical privacy settings.
