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HU Credits:
4
Degree/Cycle:
1st degree (Bachelor)
Responsible Department:
Computer Sciences
Semester:
2nd Semester
Teaching Languages:
Hebrew
Campus:
E. Safra
Course/Module Coordinator:
Ami Wiesel
Coordinator Office Hours:
Coordinate in advance
Teaching Staff:
Prof Ami Wiesel
Mr. Nisan Chiprut
Course/Module description:
One dimensional optimization problem.
Convex functions [BV 3].
Least squares [PSU 4].
Unconstrained optimization [BV 9].
Convex sets [BV 2].
Constrained optimization over a convex set [B 2].
Quiz.
Standard convex optimization [BV 4].
Duality and optimality conditions [BV 5].
Interior point methods [BV 10-‐11].
Semidefinite programming [papers].
Course/Module aims:
See learning outcomes
Learning outcomes - On successful completion of this module, students should be able to:
Identify functions and convex sets.
Formulate a convex optimization problem and solve it numerical.
Dual problem and develop optimal conditions.
Attendance requirements(%):
0
Teaching arrangement and method of instruction:
workshop
Course/Module Content:
One dimensional optimization problem.
Convex functions [BV 3].
Least squares [PSU 4].
Unconstrained optimization [BV 9].
Convex sets [BV 2].
Constrained optimization over a convex set [B 2].
Quiz.
Standard convex optimization [BV 4].
Duality and optimality conditions [BV 5].
Interior point methods [BV 10-‐11].
Semidefinite programming [papers].
Required Reading:
Recommended to read Boyd's lecture notes from Stanford.
Additional Reading Material:
NA
Course/Module evaluation:
End of year written/oral examination 80 %
Presentation 0 %
Participation in Tutorials 0 %
Project work 0 %
Assignments 0 %
Reports 0 %
Research project 0 %
Quizzes 20 %
Other 0 %
Additional information:
Boyd and Vandenberghe, Convex Optimization.
Bertsekas, Nonlinear Programming.
Peressini, Sullivan and Uhl, The Mathematics of Nonlinear programming. Nemirovski, Lecture notes.
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