Pages that link to "Item:Q2347898"
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The following pages link to New analysis of manifold embeddings and signal recovery from compressive measurements (Q2347898):
Displaying 17 items.
- Toward a unified theory of sparse dimensionality reduction in Euclidean space (Q496171) (← links)
- Dimensionality reduction with subgaussian matrices: a unified theory (Q515989) (← links)
- What happens to a manifold under a bi-Lipschitz map? (Q527443) (← links)
- Rigorous restricted isometry property of low-dimensional subspaces (Q778034) (← links)
- MRA contextual-recovery extension of smooth functions on manifolds (Q1045712) (← links)
- Stable recovery of low-dimensional cones in Hilbert spaces: one RIP to rule them all (Q1748256) (← links)
- On recovery guarantees for one-bit compressed sensing on manifolds (Q2022611) (← links)
- Compressive statistical learning with random feature moments (Q2664824) (← links)
- Quantized Compressed Sensing: A Survey (Q3296175) (← links)
- Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds (Q4570691) (← links)
- Representation and coding of signal geometry (Q4603712) (← links)
- Time for dithering: fast and quantized random embeddings via the restricted isometry property (Q4603715) (← links)
- Adaptive Geometric Multiscale Approximations for Intrinsically Low-dimensional Data (Q5214182) (← links)
- Endpoint Results for Fourier Integral Operators on Noncompact Symmetric Spaces (Q5230191) (← links)
- Lower bounds on the low-distortion embedding dimension of submanifolds of \(\mathbb{R}^n\) (Q6038821) (← links)
- On fast Johnson-Lindenstrauss embeddings of compact submanifolds of \(\mathbb{R}^N\) with boundary (Q6151027) (← links)
- Low dimensional approximation and generalization of multivariate functions on smooth manifolds using deep ReLU neural networks (Q6536393) (← links)
