Publications associées à Sparse dictionary learning

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An Adaptive Sublinear-Time Block Sparse Fourier Transform

Volkan Cevher, Mikhail Kapralov, Jonathan Mark Scarlett, Amir Zandieh

The problem of approximately computing the

k

dominant Fourier coefficients of a vector

X

quickly, and using few samples in time domain, is known as the Sparse Fourier Transform (sparse FFT) problem. A long line of work on the sparse FFT has resulted in ...

2017

Sparse dictionary learning

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An Adaptive Sublinear-Time Block Sparse Fourier Transform

Limits on Support Recovery With Probabilistic Models: An Information-Theoretic Framework

Sparse inverse problems for Fourier imaging

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Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

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Sparse Pronunciation Codes for Perceptual Phonetic Information Assessment

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Deep Convolutional Neural Network for Inverse Problems in Imaging

Subspace Regularized Dynamic Time Warping for Spoken Query Detection

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

Subspace Regularized Dynamic Time Warping for Spoken Query Detection

Limits on Support Recovery With Probabilistic Models: An Information-Theoretic Framework

Face Recognition in Real-world Images

Efficient Inversion of Multiple-Scattering Model for Optical Diffraction Tomography

Deep Convolutional Neural Network for Inverse Problems in Imaging

Sparse inverse problems for Fourier imaging

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Sparse Pronunciation Codes for Perceptual Phonetic Information Assessment

Low-rank and Sparse Soft Targets to Learn Better DNN Acoustic Models