IPAM Meeting

The IPAM meeting on Adaptive Data Analysis and Sparsity was a big success. Thank you to everyone who participated.


The GRASTAcam code is availabile for download here. This code uses OpenCV to run Grasta using the camera on your computer. It was written by Arthur Szlam (with makefile by Jia Xu, Thanks Jia!) in C using the Intel MKL library.


Grassmannian Robust Adaptive Subspace Tracking Algorithm (GRASTA), is an algorithm for subspace identification and tracking in the presence of corrupted and missing data. The algorithm is derived using the Augmented Lagrangian for an l1 cost function. See our page on GRASTA for code and a description of the algorithm.



Grassmannian Rank-One Update Subspace Estimation (GROUSE), is an online algorithm for subspace identification and tracking when data vectors are incomplete. See our page on GROUSE for details about the algorithm. GROUSE can be used for matrix completion; download grouse.m for the Matlab function and rungrouse.m to see how to run it.

Generating all rooted trees

Matlab code to enumerate all possible trees on n nodes: I wrote this awhile ago when I needed to enumerate all possible trees that could be formed by a set of n nodes. There are n^(n-1) such trees. This code uses the fact that there is a bijection between these trees and Prufer sequences. Here is tree_enumeration.m, which is a skeleton file for running code on all possible trees, and here is the function for generating the next tree, get_next_tree.m.

Compressed Sensing in Audio Signals

A demo for Compressed Sensing in Audio Signals can be found here, along with matlab code for the examples.

Blind Calibration

Blind Calibration examples and code can be found here.

Class Project Reports

Click here for class project reports for Maximum Likelihood Source Localization and an Aggregation tree in SOS and Emstar. Also, this