
Recent Posts
 There is time for dithering in a quantized world of reduced dimensionality!
 Quantized subGaussian random matrices are still RIP!
 Quasiisometric embeddings of vector sets with quantized subGaussian projections
 Testing a QuasiIsometric Quantized Embedding
 When Buffon’s needle problem meets the JohnsonLindenstrauss Lemma
Archives
Blogroll
Related Links and Blogs
Blog Stats
 16,051 hits
Category Archives: General
There is time for dithering in a quantized world of reduced dimensionality!
I’m glad to announce here a new work made in collaboration with Valerio Cambareri (UCL, Belgium) on quantized embeddings of lowcomplexity vectors, such as the set of sparse (or compressible) signals in a certain basis/dictionary, the set of lowrank matrices … Continue reading
Posted in General
Leave a comment
Quantized subGaussian random matrices are still RIP!
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
Posted in General
Leave a comment
When Buffon’s needle problem meets the JohnsonLindenstrauss Lemma
(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
Posted in Compressed Sensing, General, Johnson Lindenstrauss
1 Comment
Recovering sparse signals from sparsely corrupted compressed measurements
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 1bit compressed sensing (CS) [1]. I was wondering if these could … Continue reading
Posted in General
Leave a comment
A useless nonRIP Gaussian matrix
Recently, for some unrelated reasons, I discovered that it is actually very easy to generate a Gaussian matrix that does not respect the restricted isometry property (RIP) [1]. I recall that such a matrix is RIP if there exists a … Continue reading
Posted in Compressed Sensing, General
Leave a comment
Tomography of the magnetic fields of the Milky Way?
I have just found this “new” (well 150 years old actually) tomographical method… for measuring the magnetic field of our own galaxy “New allsky map shows the magnetic fields of the Milky Way with the highest precision“by Niels Oppermann et … Continue reading
New class of RIP matrices ?
Wouaw, almost one year and half without any post here…. Shame on me! I’ll try to be more productive with shorter posts now 😉 I just found this interesting paper about concentration properties of submodular function (very common in “Graph … Continue reading