L2G, a bilevel training objective that evaluates an inner-loop gradient update on a second disjoint task, improves Prototypical and Relation Networks by one to five accuracy points on mini-ImageNet and tiered-ImageNet.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Learning to Generalize to Unseen Tasks with Bilevel Optimization
L2G, a bilevel training objective that evaluates an inner-loop gradient update on a second disjoint task, improves Prototypical and Relation Networks by one to five accuracy points on mini-ImageNet and tiered-ImageNet.