Basic Information
-convex Optimization Problem With and Without Constraints -first Order Optimization Methods -first Order Stochastic Optimization Methods and The Sgd Algorithm -momentum Methods and Nesterov S Accelerated Methods -the Frank-wolfe Method -duality -kkt Conditions -newton S Method. Learning Outcomes# After The Successful Completion of The Course# 1. The Students Will Be Familiar With Definitions and Properties Of Optimization Problems, and Will Know to Read and Write Such Problems By Themselves._ 2. The Students Will Be Familiar With Popular Optimization Methods, Their Advantages and Their Disadvantages.
Faculty: Electrical and Computer Engineering
|Undergraduate Studies
|Graduate Studies
Pre-required courses
(104013 - Differential and Integral Calculus 2t and 104016 - Algebra 1/extended) or 104034 - Introduction to Probability H
Course with no extra credit
104193 - Optimization Theory 236330 - Introduction to Optimization
Related Books
Semestrial Information
Weekly Hours
3 Academic Credit • 2 Lecture Hours • 1 Discussion Hours
Responsible(s)
Yehuda Levy
Notes
-
מתרגל ובודק תרגילים: רון דורפמן
Exams
Session A: 09-09-2024 Session B: 08-10-2024Registration Groups
|
|
Weekly Hours
3 Academic Credit • 2 Lecture Hours • 1 Discussion Hours
Responsible(s)
Yehuda Levy
Notes
-
מתרגל ובודק תרגילים: רון דורפמן
Exams
Session A: 19-07-2023 09:00 - 12:00- אולמן 805.
- אולמן 200. 201.
Registration Groups
|
|
Weekly Hours
3 Academic Credit • 2 Lecture Hours • 1 Discussion Hours
Responsible(s)
Yehuda Levy
Notes
-
מתרגל ובודק תרגילים: רון דורפמן
Exams
Session A: 04-07-2022 13:00 - 16:00- אולמן 802.
- אולמן 500. 505.
Registration Groups
|
|