Transductive inference is an effective means of tackling the data deficiency problem in few-
shot learning settings. A popular transductive inference technique for few-shot metric-based
approaches, is to update the prototype of each class with the mean of the most confident
query examples, or confidence-weighted average of all the query samples. However, a
caveat here is that the model confidence may be unreliable, which may lead to incorrect
predictions. To tackle this issue, we propose to meta-learn the confidence for each query …