Sentence scoring aims at measuring the likelihood score of a sentence and is widely usedinnatural language processing scenarios, likereranking, which isto select the best sentence from multiple candidates.

In two layer networks, we show how feature learning can dynamically reduce the variance of the final tangent kernel and final network predictions.

Intheformer (RL),actionstaken at early stages could substantially impact the future; with regards to planning, the agent must not only consider theimmediate rewardbutalso thepossible future transitions into differing states.