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Found 3 papers, 1 papers with code
Active search and coverage using point-cloud reinforcement learning
We consider a problem in which the trajectory of a mobile 3D sensor must be optimized so that certain objects are both found in the overall scene and covered by the point cloud, as fast as possible.
Two-Channel Extended Kalman Filtering with Intermittent Measurements
In the first problem, we generalize linear-case 2C analysis to obtain -- for a given pair of channel arrival rates -- boundedness conditions for the trace of the error covariance, as well as a worst-case upper bound.
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective
We conduct ablation studies to disentangle the various effects normalisation has on the learning dynamics and show that is sufficient to modulate the parameter updates to recover most of the performance of spectral normalisation.
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