Scalable Structured Low Rank Matrix Optimization Problems

author: Marco Signoretto, KU Leuven
published: Aug. 26, 2013,   recorded: July 2013,   views: 3472


Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.


We consider a class of structured low rank matrix optimization problems. We represent the desired structure by a linear map, termed mutation, that can encode matrices having entries partitioned into known disjoined groups. Our interest arises in particular from concatenated block-Hankel matrices that appear in formulations for input-output linear system identi fication problems with noisy and/or partially unobserved data. We present an algorithm and test it against an existing alternative.

See Also:

Download slides icon Download slides: roks2013_signoretto_optimization_01.pdf (502.3┬áKB)

Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: