Igor Carron

Compressed Sensing: Near-ideal model selection by L1 mini...

Emmanuel Candes and Yaniv Plan just released this preprint on Near-ideal model selection by L1 minimization. The abstract reads: We consider the fundamental problem of estimating the mean of a vector y = X \beta + z where X is ... Read more

Compressed Sensing: Random Features for Large-Scale Kerne...

In a previous, I mentioned the potential connection between compressed sensing and the visual cortex through a model that uses random projections. At the latest NIPS conference, it looks like we are beginning to see some convergence in Random Features ... Read more

An opportunity for Opportunity ?

After some additional trajectory analysis, there is now a 1 to 25 chance of the 2007 WD5 meteorite hitting Mars on January 30th. If it hits, it will be a 30 megaton impact in a region north of where Opportunity ... Read more

Building a Roaming Dinosaur: Why is Policy Learning Not U...

Dubai is going to host a Jurassic Park. It is about time: the current display of Animatronics are very much underwhelming and certainly do not yield the type of magic moment as displayed by Laura Dern's face in Jurassic Park. ... Read more

Compressed sensing: CS for networked data, Diffusion wav...

The Special Issue on Compressive Sampling of the IEEE Signal Processing Magazine will also feature Compressed sensing for networked data by Jarvis Haupt, Waheed Bajwa, Mike Rabbat, and Robert Nowak. In the article, one can learn how one can exploit ... Read more

Compressed Sensing: How could Hardware implementations be...

I am still wondering how technology developed with Compressed Sensing could be construed at Disruptive Technology, here is reminder of what disruptive technology is: "...Disruptive technologies do not destroy existing market leaders overnight. They do not get adopted by the ... Read more

Monday Morning Algorithm 8: An Example of Compressed Meas...

In the previous installment of the Monday Morning Algorithm, we featured the diffusion method. I also mentioned that one could use compressed sensing and obtain the same result: i.e the ability to sort several high dimensional images because only one ... Read more

Compressed Sensing: Fast Compressive Sampling with Struct...

Thong Do mentions that the paper presented here is already on the Rice website. Thong Do, Trac Tran and Lu Gan are co-authors of the fascinating Fast Compressive Sampling with Structurally Random Matrices which seems to lead to highly sparse ... Read more