← Back to papers
2023 JMLR JMLR 2023

A Group-Theoretic Approach to Computational Abstraction: Symmetry-Driven Hierarchical Clustering

Abstract

Haizi Yu, Igor Mineyev, Lav R. Varshney; 24(47):1−61, 2023.

🧭 Keyword Pioneer — computational abstraction
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing
🌉 Interdisciplinary Bridge — Machine Learning and Mathematics & Optimization

Authors

Haizi Yu , Igor Mineyev , Lav R. Varshney

Topics

Machine Learning > Core Methods > Clustering Machine Learning > Core Methods > Representation Learning Mathematics & Optimization > Mathematics > Algebra

Keywords

hierarchical clustering group theory computational abstraction
Download PDF

Related papers

Flexible Model Aggregation for Quantile Regression 2023
Efficient Computation of Rankings from Pairwise Comparisons 2023
Efficient Structure-preserving Support Tensor Train Machine 2023
Attacks against Federated Learning Defense Systems and their Mitigation 2023
How Do You Want Your Greedy: Simultaneous or Repeated? 2023