STATS M232A · STAT M232AStatistical Modeling and Learning in Vision and Cognition
Statistics · 4 units · Graduate courses (200-299)
(Same as Computer Science M266A.) 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.
STATS M232A
- STATS M232CCognitive Artificial Intelligence
- COMM M232CCognitive Artificial Intelligence
2 courses list this as a requisite. The whole downstream is here — 2 courses over 1 level. Every course here opens its own tree.