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This note studies the robust output feedback stabilization problem of a class of multi-input multi-output invertible nonlinear systems, for which an "ideal" state feedback based on feedback linearization can be designed under certain mild assumptions...
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To use reinforcement learning from human feedback (RLHF) in practical applications, it is crucial to learn reward models from diverse sources of human feedback and to consider human factors involved in providing feedback of different types. However,...
In this paper, we relate a feedback channel with any finite-order autoregressive moving-average (ARMA) Gaussian noises to a variant of the Kalman filter. In light of this, we obtain relatively explicit lower bounds on the feedback capacity for such c...
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We are often asked how clinician feedback shapes our approach to training and onboarding in practice, and the answer is simple: we listen closely and translate what clinicians need into practical updates that make adoption easier. ➡ When clinicians asked for t…
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