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        <title>A Greedy Bit-flip Training Algorithm for Binarized Knowledge Graph Embeddings</title>
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    <abstract>This paper presents a simple and effective discrete optimization method for training binarized knowledge graph embedding model B-CP. Unlike the prior work using a SGD-based method and quantization of real-valued vectors, the proposed method directly optimizes binary embedding vectors by a series of bit flipping operations. On the standard knowledge graph completion tasks, the B-CP model trained with the proposed method achieved comparable performance with that trained with SGD as well as state-of-the-art real-valued models with similar embedding dimensions.</abstract>
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%0 Conference Proceedings
%T A Greedy Bit-flip Training Algorithm for Binarized Knowledge Graph Embeddings
%A Hayashi, Katsuhiko
%A Kishimoto, Koki
%A Shimbo, Masashi
%Y Cohn, Trevor
%Y He, Yulan
%Y Liu, Yang
%S Findings of the Association for Computational Linguistics: EMNLP 2020
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F hayashi-etal-2020-greedy
%X This paper presents a simple and effective discrete optimization method for training binarized knowledge graph embedding model B-CP. Unlike the prior work using a SGD-based method and quantization of real-valued vectors, the proposed method directly optimizes binary embedding vectors by a series of bit flipping operations. On the standard knowledge graph completion tasks, the B-CP model trained with the proposed method achieved comparable performance with that trained with SGD as well as state-of-the-art real-valued models with similar embedding dimensions.
%R 10.18653/v1/2020.findings-emnlp.10
%U https://aclanthology.org/2020.findings-emnlp.10
%U https://doi.org/10.18653/v1/2020.findings-emnlp.10
%P 109-114

Markdown (Informal)

[A Greedy Bit-flip Training Algorithm for Binarized Knowledge Graph Embeddings](https://aclanthology.org/2020.findings-emnlp.10) (Hayashi et al., Findings 2020)

• A Greedy Bit-flip Training Algorithm for Binarized Knowledge Graph Embeddings (Hayashi et al., Findings 2020)

ACL

• Katsuhiko Hayashi, Koki Kishimoto, and Masashi Shimbo. 2020. A Greedy Bit-flip Training Algorithm for Binarized Knowledge Graph Embeddings. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 109–114, Online. Association for Computational Linguistics.