Home > Image Processing, Machine Learning > Summer Reading Wish List

Summer Reading Wish List

I have been expecting the reading group for a long time, and now come to realize, but unfortunately, currently out of University this summer. Anyway, it’s good to follow and make some discussions remotely.
Below is the tentative list by Prof. Bouman. I was always impressed by his passion, and his lectures are just GREAT! I still remember it vividly when I was taking one of his course on image processing.

[Log]:
-05/20- The list is not complete yet. I will update it and put corresponding links for each sub-topics.

[List]:
# Compressed Sensing
1. D. Donoho – Compressed Sensing

2. Wright et. Al – Robust Face Recognition via Sparse Representation
# Image Processing and Vision
1. Peyman Milanfar – A Tour of Modern Image Filtering ( with the earlier version as ‘A Tour of Modern Image Processing’)
It’s video-lecture.
2. Zyg Pizlo – Binocular vision paper
3. Segmentation, state-of-the-art

# High-Dimensional/Sparse Methods
1. Al. Hero et. Al – Large Scale Correlation Screening

# Dictionary Learning
2. Elad – K-SVD paper
3. Some other dictionary learning paper – possibilities
a. Wolberg
b. Shapiro
4. Moody – Classification of Transient signals

# Physics Modeling and Inversion
1. Nicholas Zabaras – manifold learning
2. Marc De Graef – vector tomography for microscopy

# Dirichlet Processes
1. Michael Jordan’s Tutorial
Graphical Models
2. Need to find papers – two major topics:
a. Belief propagation Tutorial
b. Uses of graphical models

# Johnson Lindenstrauss Lemma
1. Identify good tutorial

# Regularized Discriminant Analysis
1. Friedman – Regularized Discriminant Analysis
2. Jiang – Eigenfeature Regularization and Extraction in Face Recognition
3. Hasib – Sparse Fisher’s Linear Discriminant Analysis

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