Adaptive Geometric Multiscale Approximations for Intrinsically Low-dimensional Data
From MaRDI portal
Publication:5214182
zbMath1446.68140arXiv1611.01179MaRDI QIDQ5214182
Publication date: 7 February 2020
Full work available at URL: https://arxiv.org/abs/1611.01179
Directional data; spatial statistics (62H11) Factor analysis and principal components; correspondence analysis (62H25) Learning and adaptive systems in artificial intelligence (68T05) Computational aspects of data analysis and big data (68T09)
Related Items (max. 100)
Adaptive Geometric Multiscale Approximations for Intrinsically Low-dimensional Data ⋮ Multiscale regression on unknown manifolds ⋮ Deep nonparametric estimation of intrinsic data structures by chart autoencoders: generalization error and robustness ⋮ On recovery guarantees for one-bit compressed sensing on manifolds ⋮ Unnamed Item
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
- Multi-scale geometric methods for data sets. II: Geometric multi-resolution analysis
- Foundations of a multi-way spectral clustering framework for hybrid linear modeling
- Asymptotic regularity of subdivisions of Euclidean domains by iterated PCA and iterated 2-means
- Rectifiable sets and the traveling salesman problem
- A distribution-free theory of nonparametric regression
- Hybrid linear modeling via local best-fit flats
- New analysis of manifold embeddings and signal recovery from compressive measurements
- Multiscale geometric methods for data sets. I: Multiscale SVD, noise and curvature.
- The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
- Universal algorithms for learning theory. II: Piecewise polynomial functions
- Multiscale Dictionary Learning: Non-Asymptotic Bounds and Robustness
- Sample Complexity of Dictionary Learning and Other Matrix Factorizations
- Adapting to Unknown Smoothness via Wavelet Shrinkage
- Estimation of Subspace Arrangements with Applications in Modeling and Segmenting Mixed Data
- Ten Lectures on Wavelets
- Atomic Decomposition by Basis Pursuit
- A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
- Ideal spatial adaptation by wavelet shrinkage
- Dictionary Learning Algorithms for Sparse Representation
- Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps
- Geometric diffusions as a tool for harmonic analysis and structure definition of data: Multiscale methods
- Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment
- On the importance of combining wavelet-based nonlinear approximation with coding strategies
- A T(b) theorem with remarks on analytic capacity and the Cauchy integral
- Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
- Approximation of points on low-dimensional manifolds via random linear projections
- Adaptive Geometric Multiscale Approximations for Intrinsically Low-dimensional Data
- $K$-Dimensional Coding Schemes in Hilbert Spaces
- Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data
- The Rotation of Eigenvectors by a Perturbation. III
- RELATIONS BETWEEN TWO SETS OF VARIATES
- Compressed sensing
This page was built for publication: Adaptive Geometric Multiscale Approximations for Intrinsically Low-dimensional Data