Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space-Reference-Cited by-同舟云学术

Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space

Published:2019-07-25 Issue: Volume: Page:
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Container-title:Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
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Author:

Monath Nicholas¹,Zaheer Manzil²,Silva Daniel²,McCallum Andrew¹,Ahmed Amr²

Affiliation:

1. University of Massachusetts Amherst, Amherst, MA, USA

2. Google Research, Mountain View, CA, USA

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3292500.3330997

Reference57 articles.

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3. M.F. Balcan A. Blum and S. Vempala. 2008. A discriminative framework for clustering via similarity functions. STOC. 10.1145/1374376.1374474 M.F. Balcan A. Blum and S. Vempala. 2008. A discriminative framework for clustering via similarity functions. STOC. 10.1145/1374376.1374474

4. J. Bingham and S. Sudarsanam. 2000. Visualizing large hierarchical clusters in hyperbolic space. Bioinformatics. J. Bingham and S. Sudarsanam. 2000. Visualizing large hierarchical clusters in hyperbolic space. Bioinformatics.

5. C. Blundell Y. W. Teh and K. A. Heller. 2010. Bayesian rose trees. UAI. C. Blundell Y. W. Teh and K. A. Heller. 2010. Bayesian rose trees. UAI.

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