Algorithms
Convex optimization · Standard syllabus
Gradient descent
Objectives
- Gradient descent
- Accelerated methods (Nesterov)
- Proximal methods and operator splitting
- Interior-point methods for LP
- SDP (overview)
- ADMM and Douglas–Rachford splitting
- Complexity
- Convergence rates (introduction)
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