CAP 6617, Advanced Machine Learning, Spring 2024

Instructor:
Arunava Banerjee
Office: Malachowsky Hall 6101.
E-mail: arunava@ufl.edu.
Office hours: Tuesday 12:00 p.m.-2:00 p.m.

Pre-requisites:

• One has to take CAP6610 (Machine Learning) before this course. Specifically, knowledge of calculus and linear algebra is necessary since we shall be discussing advanced topics.

Reference: Machine Learning: A Probabilistic Perspective, Murphy, ISBN-10: 0262018020.

Reference: Pattern Recognition and Machine Learning, Bishop, ISBN 0-38-731073-8.

Reference: Pattern Classification, 2nd Edition, Duda, Hart and Stork, John Wiley, ISBN 0-471-05669-3.

Tentative list of Topics to be covered

• Reproducing Kernel Hilbert Space
• Recent topics in Deep learning such as Transformers
• Dirichlet processes and non-parametric Bayesian methods.
• Manifold learning including local linear embedding, isomap, laplacian eigenmap.
• Graphical models and Variational Inference
• Monte-Carlo, Markov Chain methods (Gibbs samplers and Metropolis-Hastings)

The above list is tentative at this juncture and the set of topics we end up covering might change due to class interest and/or time constraints.

Please return to this page at least once a week to check updates in the table below

Evaluation:

• Class participation and presentations

Course Policies:

• Late assignments: All homework assignments are due before class.
• Plagiarism: You are expected to submit your own solutions to the assignments. While the final project and presentation will be done in groups, each member will be required to demonstrate his/her contribution to the work.
• Attendance: Their is no official attendance requirement. If you find better use of the time spent sitting thru lectures, please feel free to devote such to any occupation of your liking. However, keep in mind that it is your responsibility to stay abreast of the material presented in class.
• Cell Phones: Absolutely no phone calls during class. Please turn off the ringer on your cell phone before coming to class.

Academic Dishonesty: See http://www.dso.ufl.edu/judicial/honestybrochure.htm for Academic Honesty Guidelines. All academic dishonesty cases will be handled through the University of Florida Honor Court procedures as documented by the office of Student Services, P202 Peabody Hall. You may contact them at 392-1261 for a "Student Judicial Process: Guide for Students" pamphlet.

Students with Disabilities: Students requesting classroom accommodation must first register with the Dean of Students Office. The Dean of Students Office will provide documentation to the student who must then provide this documentation to the Instructor when requesting accommodation.

Announcements

Readings

Article	Due Date
ISOMAP	2024
Local Linear Embedding	2024
Reducing the Dimensionality of Data with Neural Networks	2024
A Generalized Representer Theorem	2024
Deep Belief Networks	2024
Dirichlet Process	2024
Polya Tree	2024
The Infinite Gaussian Mixture Model	2024
Laplacian Eigenmap	2024
Factor Graphs and the Sum-Product Algo	2024
Variational Inference	2024
Latent Dirichlet Allocation	2024
Understanding Metropolis Hastings	2024
Statistical view of Boosting	2024
Restricted Boltzmann Machine	2024
Transformer (Deep Learning)	2024
Diffusion Model (Deep Learning)	2024
Scoring Model (Deep Learning)	2024
Lilian Weng's Blog on diffusion models	2024
Double descent	2024
Explaining Double descent	2024

List of Topics covered

Week	Topic
Jan 08 - Jan 13	Intro and list of topics to be discussed in class.