A Fully Hyperbolic Neural Model for Hierarchical Multi-Class Classification

by   Federico López, et al.

Label inventories for fine-grained entity typing have grown in size and complexity. Nonetheless, they exhibit a hierarchical structure. Hyperbolic spaces offer a mathematically appealing approach for learning hierarchical representations of symbolic data. However, it is not clear how to integrate hyperbolic components into downstream tasks. This is the first work that proposes a fully hyperbolic model for multi-class multi-label classification, which performs all operations in hyperbolic space. We evaluate the proposed model on two challenging datasets and compare to different baselines that operate under Euclidean assumptions. Our hyperbolic model infers the latent hierarchy from the class distribution, captures implicit hyponymic relations in the inventory, and shows performance on par with state-of-the-art methods on fine-grained classification with remarkable reduction of the parameter size. A thorough analysis sheds light on the impact of each component in the final prediction and showcases its ease of integration with Euclidean layers.


page 1

page 2

page 3

page 4


Fine-Grained Entity Typing in Hyperbolic Space

How can we represent hierarchical information present in large type inve...

Large-Margin Classification in Hyperbolic Space

Representing data in hyperbolic space can effectively capture latent hie...

Hyperbolic Interaction Model For Hierarchical Multi-Label Classification

Different from the traditional classification tasks which assume mutual ...

Joint Learning of Hyperbolic Label Embeddings for Hierarchical Multi-label Classification

We consider the problem of multi-label classification where the labels l...

Hyperbolic Generative Adversarial Network

Recently, Hyperbolic Spaces in the context of Non-Euclidean Deep Learnin...

Multi-modal Entity Alignment in Hyperbolic Space

Many AI-related tasks involve the interactions of data in multiple modal...

Hierarchical Symbolic Reasoning in Hyperbolic Space for Deep Discriminative Models

Explanations for black-box models help us understand model decisions as ...