ELEC 631 - Advanced Digital Signal Processing: Deep Learning - Spring 2015
This course will explore deep learning, multistage machine learning methods that learn representations of complex data. Over the past several years, thanks for the development of new training rules, massive computing capabilities, and enormous training data sets, deep learning systems have redefined the state-of-the-art in object identification, face recognition, and speech recognition. Examples of modern tools include Facebook's Deep Face and Google's DeepMind.
Topics to be discussed include: Deep learning architectures, training deep learning systems, convolutional neural networks (CNNs), applications.
Duncan Hall 2028, 713-348-5132, email@example.com
Office hours: Wednesday, 3-4pm
Duncan Hall 2050, 7133483293, firstname.lastname@example.org
Time: Friday 1-3pm
This is a "reading course", meaning that students will read classic and recent papers and present to the rest of the class in a lively debate format. Students will also get hands on experience with deep learning software and complete a major group project. The course is open to graduate students from any department with some background in statistics or machine learning.
Class grade will be based on:
- Class participation (10%)
- Paper presentations (30%)
- Paper summaries (prepared each week, 10%)
- Software homework (20%)
- Group project (30%)
Weekly Schedule (Tentative)
- 16 January 2015: Orientation
- Late April 2015: Group Project Presentations