In this program
- Convex analysis foundations
- Convex optimization problems
- Algorithms
- Applications in science and engineering
- Implementation and case studies
Applications in science and engineering
Convex optimization · Standard syllabus
Sparse recovery
Objectives
- Sparse recovery
- Compressed sensing (L1 methods)
- Portfolio optimization
- Risk constraints
- Control: LQR and model predictive control (convex formulations)
- Signal processing
- Denoising
- Machine learning
Study materials
- Study guideComing soon
- Exam StrategyComing soon
- Common MistakesComing soon
- WorksheetsComing soon
- Word problemsComing soon
- Mixed PracticeComing soon
- Multi-Unit ProblemsComing soon
- ReviewComing soon
- Practice testComing soon
- Answer keyComing soon
Interactive practice
Quizzes, typed answers, and flashcards for this unit — coming soon.
- Coming soon
Quiz
Multiple-choice questions with instant feedback
- Coming soon
Typed practice
Type answers and check them
- Coming soon
Flashcards
Vocabulary and key facts
- Coming soon
Mixed quiz
Harder mixed review for this standard