Study guide of JKU Linz
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KUSSS
Auwea NG
Positionsanzeige
Artificial Intelligence
»
Mathematics
Inhalt
[
536MATHNUOU20
]
UE
Numerical Optimization
Versionsauswahl
Version
2020W
Workload
Education level
Study areas
Responsible person
Hours per week
Coordinating university
1,5 ECTS
B2 - Bachelor's programme 2. year
(*)
Artificial Intelligence
Sepp Hochreiter
1 hpw
Johannes Kepler University Linz
Detailed information
Original study plan
Bachelor's programme Artificial Intelligence 2020W
Objectives
These are the exercises for the corresponding lecture.
Subject
Basics of optimization
Numerical methods for solving equations
Unconstrained optimization
Cauchy's method (steepest/gradient descent)
Newton method
Conjugate gradient
Constrained optimization
Convex optimization (linear and quadratic optimization)
Criteria for evaluation
regular homeworks
Language
English
Changing subject?
No
Corresponding lecture
in collaboration with 536MATHNUOV20: VL Numerical Optimization (3 ECTS) equivalent to
536MATHNUOK19: KV Numerical Optimization (4.5 ECTS)
On-site course
Maximum number of participants
35
Assignment procedure
Direct assignment