Probabilistic Zero-shot Classification with Semantic Rankings

27 Feb 2015 Jihun Hamm Mikhail Belkin

In this paper we propose a non-metric ranking-based representation of semantic similarity that allows natural aggregation of semantic information from multiple heterogeneous sources. We apply the ranking-based representation to zero-shot learning problems, and present deterministic and probabilistic zero-shot classifiers which can be built from pre-trained classifiers without retraining... (read more)

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