A Experimental results

Analogy sampling based meta learning. In each subset, a training sample and a test sample can have analogy relation dependent on their problem categories. Different visual shape attributes are used among train and valid/test sets. O-IG ("in distribute four out center single"), L-R ("left center single right center single"), and U-D As shown in Table 5, our proposed method ("+Analogy") shows significantly Here, we provide details for all our models. ( r 64)