EE4530 Applied convex optimization
Topics: Applied convex optimization: role of convexity in optimization, convex sets and functions, Canonical convex problems (SDP, LP, QP), second-order methods, first-order methods for large-scale problems.
The course covers several basic and advanced topics in convex optimization. The goal of this course is to recognize/formulate problems as convex optimization problems and develop algorithms for moderate as well as large size problems. The course provides insights that can be used in a variety of disciplines.
This course treats:
- Background and optimization basics
- Convex sets and functions
- Canonical convex optimization problems (LP, QP, SDP)
- First-order methods (gradient, subgradient, conjugate gradient)
- Second-order methods (unconstrained and equality constrained minimization)
Teachers
prof.dr.ir. Geert Leus (SPS)
Signal processing for communications, with applications to underwater communications, cognitive radio, and multiple-input multiple-output (MIMO) systems. Signal processing for (compressive) sensing with applications to ultrasound imaging and radar. Distributed signal processing. Graph signal processing.
ir. Ids van der Werf (SPS)
audio signal processing; underwater communication
Last modified: 2025-11-04
