Learning Subspaces of Different Dimensions
From MaRDI portal
Publication:5084432
DOI10.1080/10618600.2021.2000420OpenAlexW3208577532WikidataQ116034565 ScholiaQ116034565MaRDI QIDQ5084432
Brian S. Thomas, Lizhen Lin, Kisung You, Lek-Heng Lim, Sayan Mukherjee
Publication date: 24 June 2022
Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1404.6841
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
- Fisher lecture: Dimension reduction in regression
- Learning gradients on manifolds
- Robust recovery of multiple subspaces by geometric \(l_{p}\) minimization
- The geometry of exponential families
- Differential geometry of curved exponential families. Curvatures and information loss
- Stratified exponential families: Graphical models and model selection
- A geometric analysis of subspace clustering with outliers
- Empirical graph Laplacian approximation of Laplace–Beltrami operators: Large sample results
- Shape Manifolds, Procrustean Metrics, and Complex Projective Spaces
- Communication on the Grassmann manifold: a geometric approach to the noncoherent multiple-antenna channel
- 10.1162/jmlr.2003.3.4-5.993
- Packing Lines, Planes, etc.: Packings in Grassmannian Spaces
- Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
- Classification via Bayesian Nonparametric Learning of Affine Subspaces
- Subspace clustering using ensembles of K-subspaces
- Grassmannian Packings From Operator Reed–Muller Codes
- High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics
- Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data
- On Bayes procedures
- Dispersion on a Sphere
This page was built for publication: Learning Subspaces of Different Dimensions