Clustering Noisy Signals with Structured Sparsity Using Time-Frequency Representation

1 code implementation • 18 Oct 2015 • Tom Hope, Avishai Wagner, Or Zuk

We propose a simple and efficient time-series clustering framework particularly suited for low Signal-to-Noise Ratio (SNR), by simultaneous smoothing and dimensionality reduction aimed at preserving clustering information.

Clustering Dimensionality Reduction +3

Low-Rank Matrix Recovery from Row-and-Column Affine Measurements

1 code implementation • 23 May 2015 • Avishai Wagner, Or Zuk

We propose and study a row-and-column affine measurement scheme for low-rank matrix recovery.