Abstract
Although deep neural networks are effective at extracting high-level features, classification methods usually encode an input into a vector representation via simple feature aggregation operations (e.g. pooling). Such operations limit the performance. For instance, a multi-label document may contain several concepts. In this case, one vector can not sufficiently capture its salient and discriminative content. Thus, we propose Hyperbolic Capsule Networks (HyperCaps) for Multi-Label Classification (MLC), which have two merits. First, hyperbolic capsules are designed to capture fine-grained document information for each label, which has the ability to characterize complicated structures among labels and documents. Second, Hyperbolic Dynamic Routing (HDR) is introduced to aggregate hyperbolic capsules in a label-aware manner, so that the label-level discriminative information can be preserved along the depth of neural networks. To efficiently handle large-scale MLC datasets, we additionally present a new routing method to adaptively adjust the capsule number during routing. Extensive experiments are conducted on four benchmark datasets. Compared with the state-of-the-art methods, HyperCaps significantly improves the performance of MLC especially on tail labels.- Anthology ID:
- 2020.acl-main.283
- Volume:
- Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Editors:
- Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel Tetreault
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 3115–3124
- Language:
- URL:
- https://aclanthology.org/2020.acl-main.283
- DOI:
- 10.18653/v1/2020.acl-main.283
- Cite (ACL):
- Boli Chen, Xin Huang, Lin Xiao, and Liping Jing. 2020. Hyperbolic Capsule Networks for Multi-Label Classification. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 3115–3124, Online. Association for Computational Linguistics.
- Cite (Informal):
- Hyperbolic Capsule Networks for Multi-Label Classification (Chen et al., ACL 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2020.acl-main.283.pdf