I want to train a neural network that is part of a multi-armed bandit problem. For each data sample, I have some features representing the context of the sample and there are x neurons in the output layer that represents the reward for this context for a specific action (each neuron represents an action). The issue is that for each sample, I know only the reward (the y value) for the action that was played. For all other actions, I don’t have the “ground truth” for them. What is the best practice in training my nn in that case?