- There is time for dithering in a quantized world of reduced dimensionality!
- Quantized sub-Gaussian random matrices are still RIP!
- Quasi-isometric embeddings of vector sets with quantized sub-Gaussian projections
- Testing a Quasi-Isometric Quantized Embedding
- When Buffon’s needle problem meets the Johnson-Lindenstrauss Lemma
- 16,247 hits
Author Archives: jackdurden
I’m glad to announce here a new work made in collaboration with Valerio Cambareri (UCL, Belgium) on quantized embeddings of low-complexity vectors, such as the set of sparse (or compressible) signals in a certain basis/dictionary, the set of low-rank matrices … Continue reading
I have always been intrigued by the fact that, in Compressed Sensing (CS), beyond Gaussian random matrices, a couple of other unstructured random matrices respecting, with high probability (whp), the Restricted Isometry Property (RIP) look like “quantized” version of the … Continue reading
Last January, I was honored to be invited in RWTH Aachen University by Holger Rauhut and Sjoerd Dirksen to give a talk on the general topic of quantized compressed sensing. In particular, I decided to focus my presentation on the … Continue reading
It took me a certain time to do it. Here is at least a first attempt to test numerically the validity of some of the results I obtained in “A Quantized Johnson Lindenstrauss Lemma: The Finding of Buffon’s Needle” (arXiv) I … Continue reading
(This post is related to a paper entitled “A Quantized Johnson Lindenstrauss Lemma: The Finding of Buffon’s Needle” (arxiv, pdf) that I have recently submitted for publication.) Last July, I read the biography of Paul Erdős written by Paul Hoffman … Continue reading
Last Thursday after an email discussion with Thomas Arildsen, I was thinking again to the nice embedding properties discovered by Y. Plan and R. Vershynin in the context of 1-bit compressed sensing (CS) . I was wondering if these could … Continue reading