Lectures related to Scenario optimization

Constrained Convex Optimization: Min-Max Formulation and Fenchel Conjugation

Explores constrained convex optimization with min-max formulation and Fenchel conjugation.

Optimizing Heat Recovery Systems

Explores the theory of optimizing heat recovery systems through the concept of minimum temperature difference.

Lagrange Multiplier and DuBois-Reymond Equation

Explores Lagrange multiplier method and DuBois-Reymond equation in optimization.

Equivalent formulation

Covers the concept of equivalent formulation in constrained optimization and explores the tangent cone.

Kernel SVM: Polynomial Expansion & Cover's Theorem

Explores polynomial expansion, high-dimensional spaces, Cover's Theorem, Lagrangian formulation, and practical SVM applications.

Optimization Techniques: Stochastic Gradient Descent and Beyond

Discusses optimization techniques in machine learning, focusing on stochastic gradient descent and its applications in constrained and non-convex problems.

Robust Optimization: Radiation Therapy & Support Vector Machines

Explores robust optimization in radiation therapy and support vector machines.

Constrained optimization: the basics

Covers the basics of constrained optimization, including tangent directions, trust-region subproblems, and necessary optimality conditions.

Polynomial Optimization: SOS and SDP

Explores Sum of Squares polynomials and Semidefinite Programming in Polynomial Optimization, enabling the approximation of non-convex polynomials with convex SDP.

Implicit Bias in Machine Learning

Explores implicit bias, gradient descent, stability in optimization algorithms, and generalization bounds in machine learning.

Optimal Transport: Forward-Backward Splitting

Presents a new algorithm for optimal transport problems, showing speed and performance improvements, with applications in domain adaptation and generative models.

Robust Optimization in Radiation Therapy

Explores robust optimization in radiation therapy, emphasizing dose optimization and trade-offs between nominal and robust solutions.

Shape Preservation: Optimization

Delves into shape preservation through minimizing elastic energy and optimizing centroid projection.

Nonlinear Optimization: Newton's Method

Explores nonlinear optimization, focusing on Newton's method and descent methods for finding optimal solutions efficiently.

Mirror Prox: Optimization and Norms

Explores Mirror Prox optimization, argmin function, norms, and their practical applications in optimization problems.

Lagrange Multipliers Theorem

Explores the Lagrange multipliers theorem for n>2, demonstrating its application in optimization problems with constraints.

Optimality Conditions in Linear Optimization

Covers optimality conditions, strong duality, and complementarity slackness in linear optimization.

Robust Optimization: Radiation Therapy & Support Vector Machines

Explores robust optimization in radiation therapy and support vector machines, emphasizing worst-case scenarios and the use of linear decision rules.

Optimization with Constraints: Theory and Applications

Covers the theory and applications of optimization with constraints, including key concepts and numerical methods.

Environmental Economics: Course Overview and Key Concepts

Provides an overview of environmental economics, covering course structure, key concepts, and the relationship between economic activity and environmental issues.