2022
Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes
NeurIPS 2022accept
We develop a rigorous mathematical analysis of zero-shot learning with attributes. In this setting, the goal is to label novel classes with no training data, only detectors for attributes and a description of how those attributes are correlated with the target classes, called the class-attribute mat…