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Found 6 papers, 1 papers with code
StreaMRAK a Streaming Multi-Resolution Adaptive Kernel Algorithm
With a novel sub-sampling scheme, StreaMRAK reduces memory and computational complexities by creating a sketch of the original data, where the sub-sampling density is adapted to the bandwidth of the kernel and the local dimensionality of the data.
Unsupervised Knowledge-Transfer for Learned Image Reconstruction
Deep learning-based image reconstruction approaches have demonstrated impressive empirical performance in many imaging modalities.
Estimating covariance and precision matrices along subspaces
We also show that estimation of precision matrices is almost independent of the condition number of the covariance matrix.
Computational approaches to non-convex, sparsity-inducing multi-penalty regularization
In this work we consider numerical efficiency and convergence rates for solvers of non-convex multi-penalty formulations when reconstructing sparse signals from noisy linear measurements.
Information Theory Information Theory
Nonlinear generalization of the monotone single index model
This paper deals with a nonlinear generalization of this framework to allow for a regressor that uses multiple index vectors, adapting to local changes in the responses.
Unsupervised parameter selection for denoising with the elastic net
Our analysis combines statistical learning theory with insights from regularisation theory.
