Pages that link to "Item:Q2196210"
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The following pages link to Nonasymptotic upper bounds for the reconstruction error of PCA (Q2196210):
Displaying 24 items.
- Bounds on the quality of the PCA bounding boxes (Q1028234) (← links)
- Higher-order principal component analysis for the approximation of tensors in tree-based low-rank formats (Q1728088) (← links)
- Estimating multi-index models with response-conditional least squares (Q2044313) (← links)
- Principal component analysis for multivariate extremes (Q2044326) (← links)
- Statistical analysis of Mapper for stochastic and multivariate filters (Q2082451) (← links)
- Bootstrapping the operator norm in high dimensions: error estimation for covariance matrices and sketching (Q2108486) (← links)
- Relative perturbation bounds with applications to empirical covariance operators (Q2111217) (← links)
- Non-asymptotic error bound for optimal prediction of function-on-function regression by RKHS approach (Q2131156) (← links)
- Inference in latent factor regression with clusterable features (Q2137004) (← links)
- Lower bounds for invariant statistical models with applications to principal component analysis (Q2157446) (← links)
- Efficient estimation of linear functionals of principal components (Q2176629) (← links)
- Bootstrapping max statistics in high dimensions: near-parametric rates under weak variance decay and application to functional and multinomial data (Q2196217) (← links)
- Estimating covariance and precision matrices along subspaces (Q2219236) (← links)
- Distributed estimation of principal eigenspaces (Q2284361) (← links)
- High-probability bounds for the reconstruction error of PCA (Q2307416) (← links)
- Asymptotically efficient estimation of smooth functionals of covariance operators (Q2659447) (← links)
- Compressive statistical learning with random feature moments (Q2664824) (← links)
- Certified dimension reduction in nonlinear Bayesian inverse problems (Q5082037) (← links)
- Perturbation bounds for eigenspaces under a relative gap condition (Q5210923) (← links)
- A note on the prediction error of principal component regression in high dimensions (Q6050280) (← links)
- Inference on the maximal rank of time-varying covariance matrices using high-frequency data (Q6117051) (← links)
- Deep spectral Q-learning with application to mobile health (Q6548807) (← links)
- Tangent space and dimension estimation with the Wasserstein distance (Q6594420) (← links)
- Quantitative limit theorems and bootstrap approximations for empirical spectral projectors (Q6617183) (← links)
