Linear inverse problems, classification, regression, variable selection, convex optimization, and signal processing
- Efficient classification based on sparse regression (thesis)
MSc Thesis, Department of CEIT, Amirkabir University of Technology, July 2012.
- Regression with sparse approximations of data (paper, code, poster)
P. Noorzad and B. L. Sturm
European Signal Processing Conference (EUSIPCO), 2012.
- On automatic music genre recognition by sparse representation classification using auditory temporal modulations (paper, data+code, discussion)
B. L. Sturm and P. Noorzad
Computer Music Modeling and Retrieval: Lecture Notes in Computer Sciences Series. Springer, 2012.
- SPARROW: SPARse appROximation Weighted regression
- Sparse coding and dictionary learning
- Feature learning with deep networks for image classification
- Computational learning theory
- Parametric density estimation using GMMs
- High dimensional data and dimensionality reduction
- The split Bregman method for total variation denoising
I am a master’s student in Applied Mathematics at Ryerson University. Before RU, I studied AI at AUT and defended my thesis in July 2012. At AUT, I was a member of the Image Processing and Pattern Recognition Lab led by Prof. Mohammad Rahmati. Since March 2011, I also had the opportunity to work with Prof. Bob L. Sturm of AAU-Cph on a number of ML projects. Before AUT, I studied Software Engineering at UT and graduated in June 2009.