MATH 8335 Deep Learning

This course aims to present the mathematical, statistical and computational challenges of building stable representations for high-dimensional data, such as images, text and data. Topics includes discussing recent models from both supervised and unsupervised learning, convolutional architectures, invariance learning, and non-convex optimization.

Credits

3

Prerequisite

Analysis, Probability, or Numerical Optimization, or consent of instructor.

Schedule Type

Lecture

Grading Basis

Standard Letter (A-F)