COM SCI M266A · CS M266AStatistical Modeling and Learning in Vision and Cognition
Computer Science · 4 units · Graduate courses (200-299)
(Same as Statistics M232A.) Computer vision and pattern recognition. Study of four types of statistical models for modeling visual patterns: descriptive, causal Markov, generative (hidden Markov), and discriminative. Comparison of principles and algorithms for these models; presentation of unifying picture. Introduction of minimax entropy and EM-type and stochastic algorithms for learning.
S/U or letter grading.
When it runs
Not on the schedule for any of Fall 2025 through Spring 2027. UCLA publishes only that window, so this does not mean the course is gone — check the official listing.
Requisites
Official UCLA wording
Preparation: basic statistics, linear algebra (matrix analysis), computer vision.
BruinTree reads · Preparation
needs reviewconfidence 0.00 · from textBruinTree could not read this requirement — see UCLA’s wording above.
- · could not read "basic statistics" (no course number found)
- · could not read "linear algebra (matrix analysis)" (no course number found)
- · could not read "computer vision" (no course number found)
- · no course reference could be read from this requisite
Requires
Everything that has to come before this course, not just the courses named in the requisite above.
Nothing — this is an entry point.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
No course in the catalog lists this as a requisite.