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
Gaussian Process-Based Model Predictive Control
Graph Chatbot
Related lectures (30)
Problem Solving Techniques
Covers various problem-solving techniques and their real-world applications.
Energy System Optimization
Explores energy system optimization, including heat, cost, and CO2 emissions.
Optimization with Constraints: KKT Conditions
Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.
Degree of Freedom Analysis
Explores degree of freedom analysis, redundancy, and data reconciliation in process modeling and optimization.
Linear Programming Duality
Explores the concept of duality in linear programming and its practical implications in optimization.
Optimization Techniques
Covers optimization techniques, quizzes, and grade exercises in mathematical applications.
Linear Systems: Chapters 4, 5, 6
Explores the link between linear systems and optimization through elimination and LU decomposition.
Linear Equations: Least Squares Solution
Explains how to solve linear equations using the least squares method to minimize errors in the system.
Support Vector Machines: Theory and Optimization
Delves into the theory and optimization of Support Vector Machines, including Mercer's Theorem and Lagrange Duality.
Optimization Methods: Theory Discussion
Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.
Energy Systems Optimization
Explores energy systems modeling, optimization, and cost analysis for efficient operations.
Optimization with Constraints: KKT Conditions
Covers the optimization with constraints, focusing on the Karush-Kuhn-Tucker (KKT) conditions.
Dataflow Analysis: Optimization
Explores dataflow analysis for optimization, including equations solving, live variables, reaching definitions, and very busy expressions.
Optimization methods
Covers optimization methods, focusing on gradient methods and line search techniques.
Code Optimization: Speeding-up Analyses
Explores techniques to speed up dataflow analyses and discusses the importance of node ordering and post-order traversal.
Semi-Definite Programming
Covers semi-definite programming and optimization over positive semidefinite cones.
Introduction to Optimization and Operations Research
Covers fundamental concepts of optimization and operations research, exploring real-world examples and key topics over a semester.
Newton's Method: Convergence and Criteria
Explores the Newton method for non-linear equations, discussing convergence criteria and stopping conditions.
Predicting Completion Time: Optimization Strategies
Discusses predicting completion time and optimizing activities through efficient orchestration strategies and experiment-based completion curve predictions.
Optimizing Recursive Queries
Explores optimizing recursive queries in database systems using Datalog and semirings, discussing the challenges and solutions in data analytics.
Previous
Page 1 of 2
Next