| Course ID: | CSCI 8955. 4 hours. |
| Course Title: | Advanced Data Analytics: Statistical Learning and Optimization |
Course
Description: | Advanced topics in data analysis, with an emphasis on
statistical learning and related optimization problems. The
applications include regression, classification, and other tasks
in image analysis. The lectures will be based on books and
articles in the field of computer vision and medical image
analysis. |
| Oasis Title: | Advanced Data Analytics |
| Prerequisite: | CSCI 4150/6150 or CSCI 4380/6380 or permission of department. |
Semester Course
Offered: | Not offered on a regular basis. |
| Grading System: | A-F (Traditional) |
|
| Course Objectives: | After completion of this course, students will be able to:
1. Become familiar with some advanced learning algorithms and
techniques and their applications.
2. Understand methodology and use tools to apply learning
algorithms to real data and evaluate their performance.
3. Develop programs to solve classification, regression,
reconstruction, and segmentation tasks.
4. Understand the theory of optimization methods and describe
solution methods in optimization.
5. Determine when an appropriate optimization technique should
be selected and apply optimization techniques in problems
of image analysis. |
| Topical Outline: | 1. Image and shape regression for cross-sectional and
longitudinal data.
2. Sparse representation, dictionary learning, and low-rank
approximation.
3. Random forests: classification forests and regression forests.
4. Deep learning: convolutional neural networks (CNNs),
recurrent neural networks (RNNs), and Autoencoders. |