Generalization Error Bound for Hyperbolic Ordinal Embedding
Atsushi Suzuki,
Atsushi Nitanda,
Jing Wang
et al.
Abstract:Hyperbolic ordinal embedding (HOE) represents entities as points in hyperbolic space so that they agree as well as possible with given constraints in the form of entity i is more similar to entity j than to entity k. It has been experimentally shown that HOE can obtain representations of hierarchical data such as a knowledge base and a citation network effectively, owing to hyperbolic space's exponential growth property. However, its theoretical analysis has been limited to ideal noiseless settings, and its ge… Show more
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