Spring 2024
COMPSCI C281B 001 - LEC 001
Advanced Topics in Learning and Decision Making
Ryan Tibshirani, Seunghoon Paik
Class #:31974
Units: 3
Instruction Mode:
In-Person Instruction
Offered through
Electrical Engineering and Computer Sciences
Current Enrollment
Total Open Seats:
-7
Enrolled: 7
Waitlisted: 0
Capacity: 0
Waitlist Max: 10
No Reserved Seats
Also offered as:
STAT C241B
Hours & Workload
3 hours of instructor presentation of course materials per week, and 6 hours of outside work hours per week.
Other classes by Ryan Tibshirani
Other classes by Seunghoon Paik
Course Catalog Description
Recent topics include: Graphical models and approximate inference algorithms. Markov chain Monte Carlo, mean field and probability propagation methods. Model selection and stochastic realization. Bayesian information theoretic and structural risk minimization approaches. Markov decision processes and partially observable Markov decision processes. Reinforcement learning.
Class Notes
* This class is cross listed. Interested students should enroll in STAT C241B.
Rules & Requirements
Requisites
- Graduate students NOT in the Master of Engineering Program other those in EECS
Repeat Rules
Course is not repeatable for credit.
Reserved Seats
Current Enrollment
No Reserved Seats
Textbooks & Materials
See class syllabus or https://calstudentstore.berkeley.edu/textbooks for the most current information.
Guide to Open, Free, & Affordable Course Materials
Associated Sections
None