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Lecture
Optimization Programs: Piecewise Linear Cost Functions
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Related lectures (48)
Equality and Inequality Constraints: Optimization Conditions
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Covers necessary optimality conditions for optimization with constraints and discusses cones and polar sets.
Proximal Gradient Descent: Optimization Techniques in Machine Learning
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Discusses proximal gradient descent and its applications in optimizing machine learning algorithms.
Dynamic Programming: Steinitz Sequence
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Explores dynamic programming with the Steinitz sequence to optimize solutions efficiently.
Faster Gradient Descent: Projected Optimization Techniques
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Optimization Techniques: Gradient Descent and Convex Functions
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Single Inequality or Equality Constraint
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Covers single inequality or equality constraints and necessary optimality conditions in optimization problems.
Semi-Definite Programming
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Covers semi-definite programming and optimization over positive semidefinite cones.
Optimization Principles
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Linear Programming: Solving LPs
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Covers the process of solving Linear Programs (LPs) using the simplex method.
Convex Relaxation: Negative Type Theorems
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Linear Programming Basics
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Covers deriving basic linear program representation, finding solutions, and exploring optimality.
The Geometry of Linear Optimization
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Delves into linear optimization formulation, capacity expansion, investment under taxation, and revenue management in various industries.
Convex Functions: Theory and Applications
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Explores convex functions, affine transformations, pointwise maximum, minimization, Schur's Lemma, and relative entropy in mathematical optimization.
Convex Optimization: Sets and Functions
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Introduces convex optimization through sets and functions, covering intersections, examples, operations, gradient, Hessian, and real-world applications.
Multistage Games: Extensive Form and Feedback Strategies
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Optimization in Engineering
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Lagrangian Duality: Convex Optimization
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Explores Lagrangian duality in convex optimization, transforming problems into min-max formulations and discussing the significance of dual solutions.
Two-phase Simplex Algorithm: Introduction and Duality
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Introduces the two-phase simplex algorithm and explores duality in linear programming.
Convex Optimization Problems: Standard Form
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Convex Polyhedra and Linear Programs
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