most citedCombining Deep Universal Features, Semantic Attributes, and Hierarchical Classification for Zero-Shot Learning

2 citations · 4 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2020★ 2 cited

Incorrect by Construction: Fine Tuning Neural Networks for Guaranteed Performance on Finite Sets of Examples

Ivan Papusha, Rosa Wu, Joshua Brulé +3

There is great interest in using formal methods to guarantee the reliability of deep neural networks. However, these techniques may also be used to implant carefully selected input…

cs.CV2017★ 2 cited

Combining Deep Universal Features, Semantic Attributes, and Hierarchical Classification for Zero-Shot Learning

Jared Markowitz, Aurora C. Schmidt, Philippe M. Burlina +1

We address zero-shot (ZS) learning, building upon prior work in hierarchical classification by combining it with approaches based on semantic attribute estimation. For both non-nov…