Lectures related to Linear constraints: Standard form

Optimization with Constraints: KKT Conditions

Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.

Linear Optimization Techniques: Problem Solving Approaches

Provides an overview of linear optimization techniques, focusing on problem-solving methods and the importance of constraints and objective functions.

Optimization with Constraints: KKT Conditions Explained

Covers the KKT conditions for optimization with constraints, detailing their application and significance in solving constrained problems.

Constraint Satisfaction: Formulation and Algorithms

Covers the formulation of constraint satisfaction problems and systematic algorithms for solving them efficiently.

Linear Constraints: Elimination of Variables

Explains linear constraints and variable elimination in optimization problems, illustrating the process step by step.

Linear Programming Basics

Covers the basics of linear programming, defining corners, extreme points, and feasible solutions within polyhedrons.

Constraints and Lagrange

Introduces constraints, Lagrange multipliers, and generalized coordinates in physics.

Two-phase Simplex Algorithm: Introduction and Duality

Introduces the two-phase simplex algorithm and explores duality in linear programming.

Relations Between Events

Explores relations between events, disjunctive constraints, and modeling with binary variables in optimization problems.

Optimization Methods: Theory Discussion

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Automated Planning: Modeling and Constraints

Explores automated planning, constraints, and applications in diverse domains, emphasizing the challenges and efficiency of solving planning problems.

Extremum of a Function: Constraints

Explores extremum of a function under constraints and finding candidate points in practice.

Simplex Algorithm

Covers the Simplex algorithm for function minimization with linear constraints.

ALM with Inequalities: Next Steps in Optimization

Explores the Augmented Lagrangian Method with equality and inequality constraints in optimization, emphasizing the importance of slack variables.

Linear Programming: Extreme Points

Explores extreme points in linear programming and the role of constraints in finding optimal solutions.

Linear Optimization: Fundamentals

Covers the basics of linear optimization, including equations, polyhedrons, feasible directions, and optimal solutions.

Linear Programming: Weighted Bipartite Matching

Covers linear programming, weighted bipartite matching, and vertex cover problems in optimization.

Optimization: Constrained Volume Problems

Explores constrained volume problems using Lagrange multipliers to find extrema under constraints in various examples.

Security and Privacy Challenges in IoT Era

Discusses security challenges in IoT, covering bug injection, code hardening, and testing techniques.

Optimization in Energy Systems

Explores optimization in energy systems, focusing on decision-making through objective functions and constraints to determine system states.