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New PolyILR method decomposes compositional data with hierarchical structures

Researchers have introduced PolyILR, a novel method for decomposing compositional data that accounts for hierarchical structures. This technique creates a canonical orthonormal decomposition of the Aitchison tangent space, aligning with any tree topology. PolyILR yields stable and interpretable features, enabling inference at various tree resolutions and showing potential applications in probabilistic modeling. AI

IMPACT Introduces a new method for analyzing complex datasets, potentially improving machine learning model performance on hierarchical data.

RANK_REASON The cluster contains a research paper detailing a new method for data decomposition.

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COVERAGE [3]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Tree-Structured Orthonormal Decomposition of the Aitchison Simplex

    Compositional data -- vectors encoding relative proportions -- arise across scientific domains, including ecology, geochemistry, and genomics. The features in these data often come with known hierarchical structure (e.g., taxonomies, phylogenies, ontologies), yet existing methods…

  2. arXiv stat.ML TIER_1 English(EN) · Daisuke Yamada, Qijun Zhang, Travis Pence, Barbara B. Bendlin, Federico Rey, Vikas Singh ·

    Tree-Structured Orthonormal Decomposition of the Aitchison Simplex

    arXiv:2606.11646v1 Announce Type: cross Abstract: Compositional data -- vectors encoding relative proportions -- arise across scientific domains, including ecology, geochemistry, and genomics. The features in these data often come with known hierarchical structure (e.g., taxonomi…

  3. arXiv stat.ML TIER_1 English(EN) · Vikas Singh ·

    Tree-Structured Orthonormal Decomposition of the Aitchison Simplex

    Compositional data -- vectors encoding relative proportions -- arise across scientific domains, including ecology, geochemistry, and genomics. The features in these data often come with known hierarchical structure (e.g., taxonomies, phylogenies, ontologies), yet existing methods…