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CS 6962 Decomposition Techniques for Data and Computational Science  

Fall 2023

Instructor: Professor Chris Johnson (crj [at] sci.utah.edu, 4692 WEB)

Course Description: Researchers in a variety of fields collect measurements, observe data, perform simulations and use a wide range of techniques to describe, classify, analyze and draw conclusions from these data. Selecting appropriate techniques and understanding their advantages and disadvantages is an important component of data analysis. In particular, in this age of big data, large data sets provide distinct challenges given that many of the general techniques for small data sets do not scale to larger problems and are often prohibitively expensive from a computational perspective. In this class, we will survey several decomposition techniques for data and computational science applications including: Principle component analysis, independent component analysis, singular value decomposition, non-negative matrix factorization, low-rank methods, and probabilistic factorization methods.

Lectures: Mon/Wed, 1:25pm - 2:45pm, 2760 WEB

Office Hours:

  Professor Johnson: Mondays between 3:00 - 4:00 p.m. and by appointment


Dr. Timbwaoga Aime Judicael Ouermi (TAJO) (touermi [at] sci.utah.edu) , Office Hour: Wednesdays between 3:00 - 4:00 p.m. in WEB 2807.


Krishna Teja Chadalavada (chkrishnateja007 [at] gmail.com) , TBA

Class Information

Mailing Lists:

cs6962 [at] sci.utah.edu: class list. Emails to this list go to all the students. Only registered users can email to the list.

teach-cs6962 [at] sci.utah.edu: instructor list. Emails sent to this list go to all the instructors.

When class material questions are sent to the instructor email list, we will isolate the question and post the response to the class list (so that all can learn from both the question and answer).

Disability Notice

 The University of Utah seeks to provide equal access to its programs, services and activities for people with disabilities.  If you will need accommodations in the class, reasonable prior notice needs to be given to the Center for Disability Services, 162 Olpin Union Building, 581-5020 (V/TDD).  CDS will work with you and the instructor to make arrangements for accommodations.

All written information in this course can be made available in alternative format with prior notification to the Center for Disability Services.