Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Linear Matrix Inequalities: Control Networks
Graph Chatbot
Related lectures (31)
Optimization Principles
Covers optimization principles, including linear optimization, networks, and concrete research examples in transportation.
Approximation Algorithms
Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.
Duality: Duality in Linear Optimization
Covers the concept of linear optimization and the duality relationship between primal and dual problems.
Primal-dual optimization: Theory and Computation
Explores primal-dual optimization, conjugation of functions, strong duality, and quadratic penalty methods in data mathematics.
Optimization with Constraints: KKT Conditions
Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.
Optimality Conditions in Linear Optimization
Covers optimality conditions, strong duality, and complementarity slackness in linear optimization.
Robust Optimization: Polynomial Approximation & Uncertainty Sets
Explores robust optimization through polynomial approximation and uncertainty sets, including robust linear programs and optimization tricks.
SVM for Non-separable Datasets
Explains SVM for non-separable datasets, introducing slack variables and optimizing the margin for classification.
Mixing Tank: Process Control
Covers the process control of a mixing tank and optimizing its performance.
Asset Pricing and Hedging in Complete Markets
Covers asset pricing, hedging, American claims, stopping times, and dynamic programming in finance.
Linear Optimization: Active Constraints
Explores the significance of active constraints in linear optimization, showcasing how they influence the simplification of problems by focusing on relevant constraints.
Previous
Page 2 of 2
Next