EC ENGR 210B
Inference over Networks
Electrical and Computer Engineering · 4 units · Graduate courses (200-299)
Adaptation, learning, estimation, and detection over networks. Steepest-descent algorithms, stochastic-gradient algorithms, convergence, stability, tracking, and performance analyses. Distributed optimization. Online and distributed adaptation and learning. Synchronous and asynchronous network behavior. Incremental, consensus, diffusion, and gossip strategies.
Letter grading.
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Requisites
Official UCLA wording
Preparation: prior training in probability theory, random processes, linear algebra, and adaptation. Enforced requisite: course 210A.
BruinTree reads · Preparation
needs reviewconfidence 0.00 · from textBruinTree could not read this requirement — see UCLA’s wording above.
- · could not read "prior training in probability theory" (no course number found)
- · could not read "random processes" (no course number found)
- · could not read "linear algebra" (no course number found)
- · could not read "adaptation" (no course number found)
- · no course reference could be read from this requisite
BruinTree reads · Prerequisite
confidence 1.00 · from textRequires
Everything that has to come before this course, not just the courses named in the requisite above.
EC ENGR 210B
- EC ENGR 210AAdaptation and Learning
- EC ENGR 205AMatrix Analysis for Scientists and Engineers
- EC ENGR 241AStochastic Processes
1 direct requisite. Showing 4 courses over 3 levels; the branches marked with a count carry on past it. Every course here opens its own tree.
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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.