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Showing 1 to 2 of 2 for “"multi-arm bandits"”.

  1. Optimizing deep learning networks using multi-armed bandits

    … for pruning that utilize a framework, known as a multi-armed bandit, which has been successfully applied in applications where there is a need to learn which option to select given the outcome of trials. There are several different multi-arm bandit methods, and these have been used to develop new …

    salford Repository record for Optimizing deep learning networks using multi-armed bandits (opens in a new tab)

  2. Learning Heterogeneous Resource-Constrained Task Allocation Using Concurrent Multi-Task Bandits

    Task allocation is a critical aspect of multi-robot coordination, enabling the completion of complex tasks that would be intractable for individual robots. However, existing approaches to task allocation often assume that task requirements or reward functions are known and explicitly specified by …

    gatech Repository record for Learning Heterogeneous Resource-Constrained Task Allocation Using Concurrent Multi-Task Bandits (opens in a new tab)