Probabilistic HD-CB outperforms binarized HD-CB and approaches full HD-CB performance on synthetic benchmarks using as few as 3 bits per component via random partial updates with time-decaying probability.
Efficient implementation of LinearUCB through algo- rithmic improvements and vector computing acceleration for embedded learning systems,
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Contextual Bandits for Resource-Constrained Devices using Probabilistic Learning
Probabilistic HD-CB outperforms binarized HD-CB and approaches full HD-CB performance on synthetic benchmarks using as few as 3 bits per component via random partial updates with time-decaying probability.