## University COVID-19 update

### Questions about buildings and services? Visit the list of Modified Services.

Please note: The University of Waterloo is closed for all events until further notice.

# Tutte seminar - Fatma Kilinc-Karzan

Friday, February 15, 2013 — 3:30 PM to 4:30 PM EST

## On Unified View of Nullspace-type Conditions for Sparse and Low-rank Recoveries

Speaker: Fatma Kilinc-Karzan Carnegie Mellon University Mathematics and Computer Building (MC) 5158

### Abstract:

We discuss a general notion of ~Ssparsity structure~T and present a unified framework for the recovery of "sparse-structured" signals from their linear image of reduced dimension possibly corrupted with noise. This unified treatment covers usual sparse and block-sparse recoveries via commonly used $\ell_1$ regularization as well as low-rank matrix reconstruction via nuclear norm minimization. We present null-space type sufficient conditions for the recovery to be precise in the noiseless case, derive error bounds for imperfect recovery (nearly sparse signal, presence of observation noise) and relate to the other well-known conditions (Restricted Isometry Property, Mutual Incoherence) from the literature. Our emphasis is on efficiently verifiable sufficient conditions on the problem parameters (sensing matrix and sparsity structure) for the validity of the associated nullspace properties. While the efficient verifiability of a condition is by no means necessary for the condition to be meaningful and useful, we believe that verifiability has its value and is worthy of being investigated. In particular, verifiability allows us to design new recovery routines with explicit confidence bounds for the recovery error, which can then be optimized over the method parameters leading to recovery procedures with improved statistical properties.

Parts of this are joint work with Anatoli Juditsky, Arkadi Nemirovski and Boris Polyak.

Location
MC - Mathematics & Computer Building
5158
200 University Avenue West

Waterloo, ON N2L 3G1

### May 2021

S M T W T F S
25
26
27
28
29
30
1
2
3
4
5
6
7
8
9
11
12
13
15
16
18
19
22
23
24
25
26
27
28
29
30
31
1
2
3
4
5
1. 2021 (45)
1. May (5)
2. April (9)
3. March (13)
4. February (8)
5. January (10)
2. 2020 (119)
1. December (5)
2. November (12)
3. October (12)
4. September (12)
5. August (11)
6. July (17)
7. June (11)
8. May (6)
9. March (11)
10. February (11)
11. January (11)
3. 2019 (167)
4. 2018 (136)
5. 2017 (103)
6. 2016 (137)
7. 2015 (136)
8. 2014 (88)
9. 2013 (48)
10. 2012 (39)
11. 2011 (36)
12. 2010 (40)
13. 2009 (40)
14. 2008 (39)
15. 2007 (15)