Course Information
Lecture: Mon and Wed 10:00-11:30 AM at McDonnell 362
Instructor: Ulugbek Kamilov
Room: Jolley 532
Email: kamilov@wustl.edu
Office hour: Fri 2:00-3:00 PM.
Assistant instructor: Yu Sun
Room: Jolley 539
Email: sun.yu@wustl.edu
Office hours: Tue 10:00 AM-12:00 PM.
Syllabus: download (PDF).
Announcements
- Project final presentation schedule is here
- Project teams can be verified here
- Piazza page of the class is live. Sign up here
- Project guidelines are available here
- Project reports will only be collected via Gradescope (use code: 9K3G7R)
Lecture Notes
- Week 01 – 27 Aug 2018 – Mon – Course Introduction
- Week 01 – 29 Aug 2018 – Wed – Digital Image Processing and Bases and Frames
- Week 02 – 03 Sep 2018 – Mon – No class (Labor day)
- Week 02 – 05 Sep 2018 – Wed – Transforms
- Week 03 – 10 Sep 2018 – Mon – Underdetermined systems
- Week 03 – 12 Sep 2018 – Wed – Algorithmic considerations
- Week 04 – 17 Sep 2018 – Mon – Statistical inference
- Week 04 – 19 Sep 2018 – Wed – Student lectures [1] and [2]
- Week 05 – 24 Sep 2018 – Mon – Uncertainty principles
- Week 05 – 26 Sep 2018 – Wed – Student lectures [3] and [4]
- Week 06 – 01 Oct 2018 – Mon – Uniqueness of Sparse Solutions
- Week 06 – 03 Oct 2018 – Wed – Student lectures [5] and [6]
- Week 07 – 08 Oct 2018 – Mon – No class
- Week 07 – 10 Oct 2018 – Wed – Student lectures [7] and [8]
- Week 08 – 15 Oct 2018 – Mon – No class (Fall break)
- Week 08 – 17 Oct 2018 – Wed – Student lectures [9] and [10]
- Week 09 – 22 Oct 2018 – Mon – Exact recovery via basis pursuit
- Week 09 – 24 Oct 2018 – Wed – Student lectures [11] and [12]
- Week 10 – 29 Oct 2018 – Mon – Exact recovery via basis pursuit (cont)
- Week 10 – 31 Oct 2018 – Wed – Student lectures [13] and [14]
- Week 11 – 05 Nov 2018 – Mon – Exact recovery via basis pursuit (cont)
- Week 11 – 07 Nov 2018 – Wed – Student lectures [15] and [16]
- Week 12 – 12 Nov 2018 – Mon – Sparsity-driven optimization using ISTA
- Week 12 – 14 Nov 2018 – Wed – Student lectures [17] and [18]
- Week 13 – 19 Nov 2018 – Mon – Student lectures [19] and [20]
- Week 13 – 21 Nov 2018 – Wed – No class (Thanksgiving break)
- Week 14 – 26 Nov 2018 – Mon – Proximal algorithms
- Week 14 – 28 Nov 2018 – Wed – Project work
- Week 15 – 03 Dec 2018 – Mon – Final presentations: Groups (12) (04) (08) (10) (03) (11)
- Week 15 – 05 Dec 2018 – Wed – Final presentations: Groups (01) (06) (02) (05) (09) (07)
Student Lectures
- Week 04 – 19 Sep 2018 – Wed – Compressive sensing
- Week 04 – 19 Sep 2018 – Wed – Sparse MRI
- Week 05 – 26 Sep 2018 – Wed – Reweighted l1-minimization
- Week 05 – 26 Sep 2018 – Wed – Compressive sensing and compression
- Week 06 – 03 Oct 2018 – Wed – Fast ISTA (FISTA)
- Week 06 – 03 Oct 2018 – Wed – Variable splitting and ADMM
- Week 07 – 10 Oct 2018 – Wed – Total variation (TV)
- Week 07 – 10 Oct 2018 – Wed – Total generalized variation (TGV)
- Week 08 – 17 Oct 2018 – Wed – Dictionary learning
- Week 08 – 17 Oct 2018 – Wed – Convolutional dictionary learning
- Week 09 – 24 Oct 2018 – Wed – Online learning
- Week 09 – 24 Oct 2018 – Wed – Learned ISTA (LISTA)
- Week 10 – 31 Oct 2018 – Wed – Super-resolution CNN (SR-CNN)
- Week 10 – 31 Oct 2018 – Wed – Trainable nonlinear reaction diffusion (TNRD)
- Week 11 – 07 Nov 2018 – Wed – Plug-and-play priors
- Week 11 – 07 Nov 2018 – Wed – Regularization by denoising (RED)
- Week 12 – 14 Nov 2018 – Wed – Bayesian compressive sensing
- Week 12 – 14 Nov 2018 – Wed – Approximate message passing (AMP)
- Week 13 – 19 Nov 2018 – Mon – Using trained CNNs as priors
- Week 13 – 19 Nov 2018 – Mon – Deep image prior (DIP)
Documents
Optional assignments
- Assignment #1 (due on Mon, 24 Sep 2018) — Solution #1