4 papers
Geometric Scattering on Measure Spaces
Joyce Chew, Matthew Hirn, Smita Krishnaswamy +5
The scattering transform is a multilayered, wavelet-based transform initially introduced as a model of convolutional neural networks (CNNs) that has played a foundational role in o…
Gaussian Approximation for the Moving Averaged Modulus Wavelet Transform and its Variants
Gi-Ren Liu, Yuan-Chung Sheu, Hau-Tieng Wu
The moving average of the complex modulus of the analytic wavelet transform provides a robust time-scale representation for signals to small time shifts and deformation. In this wo…
When Locally Linear Embedding Hits Boundary
Hau-tieng Wu, Nan Wu
Based on the Riemannian manifold model, we study the asymptotic behavior of a widely applied unsupervised learning algorithm, locally linear embedding (LLE), when the point cloud i…
Data-Driven optimal shrinkage of singular values under high-dimensional noise with separable covariance structure with application
Pei-Chun Su, Hau-Tieng Wu
We develop a data-driven optimal shrinkage algorithm for matrix denoising in the presence of high-dimensional noise with a separable covariance structure; that is, the noise is col…