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00:30:02

Computational Economics WS 2022/23, Teil 12

Computational Economics WS 2022/23, Teil 12

Pradyumn Shukla

Computational Economics WS 2022/23

Computational Economics WS 2022/23

Pradyumn Shukla

01:21:52

Homo oeconomicus - Problem oder Lösung?

Homo oeconomicus - Problem oder Lösung?

Dirk Specht

00:16:13

Computational Economics WS 2022/23, Teil 4

Computational Economics WS 2022/23, Teil 4

Pradyumn Shukla

00:17:19

Computational Economics WS 2022/23, Teil 5

Computational Economics WS 2022/23, Teil 5

Pradyumn Shukla

00:25:48

Computational Economics WS 2022/23, Teil 8

Computational Economics WS 2022/23, Teil 8

Pradyumn Shukla

00:15:33

Computational Economics WS 2022/23, Teil 7

Computational Economics WS 2022/23, Teil 7

Pradyumn Shukla

00:21:11

Computational Economics WS 2022/23, Teil 6

Computational Economics WS 2022/23, Teil 6

Pradyumn Shukla

00:26:38

Computational Economics WS 2022/23, Teil 3

Computational Economics WS 2022/23, Teil 3

Pradyumn Shukla

00:30:26

Computational Economics WS 2022/23, Teil 2

Computational Economics WS 2022/23, Teil 2

Pradyumn Shukla

00:50:26

Computational Economics WS 2022/23, Teil 9

Computational Economics WS 2022/23, Teil 9

Pradyumn Shukla

00:54:47

Computational Economics WS 2022/23, Teil 10

Computational Economics WS 2022/23, Teil 10

Pradyumn Shukla

00:53:33

Computational Economics WS 2022/23, Teil 11

Computational Economics WS 2022/23, Teil 11

Pradyumn Shukla

00:22:11

Filmische Inszenierung und Aushandlung von KI am Beispiel von Ex Machina und Real Humans

Filmische Inszenierung und Aushandlung von KI am Beispiel von Ex Machina und Real Humans

Marie-Hélène Adam

00:12:50

Computational Economics WS 2022/23, Teil 1

Computational Economics WS 2022/23, Teil 1

Pradyumn Shukla

01:17:38

Wissenschaftsjournalismus

Wissenschaftsjournalismus

Annette Leßmöllmann

00:43:30

Wissenschafts-PR

Wissenschafts-PR

Annette Leßmöllmann

00:42:45

Mixed-Integer Optimization II, Section 3.4 (Generalized Benders decomposition, Introduction)

Mixed-Integer Optimization II, Section 3.4 (Generalized Benders decomposition, Introduction)

Oliver Stein

00:28:55

Mixed-Integer Optimization II, Section 3.5.2 (Feasibility cuts)

Mixed-Integer Optimization II, Section 3.5.2 (Feasibility cuts)

Oliver Stein

00:32:55

Mixed-Integer Optimization II, Section 3.5.4 (Cutting plane method for MICP), part 2

Mixed-Integer Optimization II, Section 3.5.4 (Cutting plane method for MICP), part 2

Oliver Stein

00:19:16

Mixed-Integer Optimization II, Section 3.6.1 (Lagrange relaxation, construction and relaxation property)

Mixed-Integer Optimization II, Section 3.6.1 (Lagrange relaxation, construction and relaxation property)

Oliver Stein

00:51:42

Mixed-Integer Optimization II, Section 3.6.4 (A subgradient method)

Mixed-Integer Optimization II, Section 3.6.4 (A subgradient method)

Oliver Stein

00:19:56

Mixed-Integer Optimization II, Section 3.5.3 (Optimality cuts)

Mixed-Integer Optimization II, Section 3.5.3 (Optimality cuts)

Oliver Stein

00:25:02

Mixed-Integer Optimization II, Section 3.7.3 (Pricing)

Mixed-Integer Optimization II, Section 3.7.3 (Pricing)

Oliver Stein

00:51:06

Mixed-Integer Optimization II, Section 3.7.1 (Dantzig-Wolfe decomposition, motivation and construction)

Mixed-Integer Optimization II, Section 3.7.1 (Dantzig-Wolfe decomposition, motivation and construction)

Oliver Stein

00:47:05

Mixed-Integer Optimization II, Section 3.8.3 (Feasibility pump), Section 3.8.4 (Metaheuristics)

Mixed-Integer Optimization II, Section 3.8.3 (Feasibility pump), Section 3.8.4 (Metaheuristics)

Oliver Stein

00:52:29

Mixed-Integer Optimization II, Section 3.5.1 (Motivation of the Outer Approximation method)

Mixed-Integer Optimization II, Section 3.5.1 (Motivation of the Outer Approximation method)

Oliver Stein

00:24:59

Mixed-Integer Optimization II, Section 3.8.1 (Diving heuristics), Section 3.8.2 (Local branching)

Mixed-Integer Optimization II, Section 3.8.1 (Diving heuristics), Section 3.8.2 (Local branching)

Oliver Stein

00:57:54

Mixed-Integer Optimization II, Section 3.7.2 (Column generation)

Mixed-Integer Optimization II, Section 3.7.2 (Column generation)

Oliver Stein

00:41:55

Mixed-Integer Optimization II, Section 3.7.4 (Initialization)

Mixed-Integer Optimization II, Section 3.7.4 (Initialization)

Oliver Stein

01:06:18

Mixed-Integer Optimization II, Section 3.5.4 (Cutting plane method for MICP), part 1

Mixed-Integer Optimization II, Section 3.5.4 (Cutting plane method for MICP), part 1

Oliver Stein

00:22:12

Mixed-Integer Optimization II, Section 3.6.2 (Decomposition by Lagrange relaxation)

Mixed-Integer Optimization II, Section 3.6.2 (Decomposition by Lagrange relaxation)

Oliver Stein

01:08:07

Mixed-Integer Optimization II, Section 3.6.3 (Comparison to continuous relaxation)

Mixed-Integer Optimization II, Section 3.6.3 (Comparison to continuous relaxation)

Oliver Stein

00:36:33

Mixed-Integer Optimization II, Section 3.4.6 (Feasibility cuts)

Mixed-Integer Optimization II, Section 3.4.6 (Feasibility cuts)

Oliver Stein

00:48:55

Mixed-Integer Optimization II, Section 3.4.7 (Cutting plane method for MICP), part 1

Mixed-Integer Optimization II, Section 3.4.7 (Cutting plane method for MICP), part 1

Oliver Stein

00:40:23

Mixed-Integer Optimization II, Section 3.4.7 (Cutting plane method for MICP), part 2

Mixed-Integer Optimization II, Section 3.4.7 (Cutting plane method for MICP), part 2

Oliver Stein

00:53:04

Mixed-Integer Optimization II, Section 3.4.5 (Optimality cuts), part 2

Mixed-Integer Optimization II, Section 3.4.5 (Optimality cuts), part 2

Oliver Stein

00:51:52

Mixed-Integer Optimization II, Section 3.4.5 (Optimality cuts), part 3

Mixed-Integer Optimization II, Section 3.4.5 (Optimality cuts), part 3

Oliver Stein

01:01:23

Mixed-Integer Optimization II, Section 3.4.3 (A functional description of the reduced feasible set)

Mixed-Integer Optimization II, Section 3.4.3 (A functional description of the reduced feasible set)

Oliver Stein

00:15:13

Mixed-Integer Optimization II, Section 3.4.4 (A purely discrete problem equivalent to MICP)

Mixed-Integer Optimization II, Section 3.4.4 (A purely discrete problem equivalent to MICP)

Oliver Stein

01:04:12

Mixed-Integer Optimization II, Section 3.2 (Continuous relaxation and rounding)

Mixed-Integer Optimization II, Section 3.2 (Continuous relaxation and rounding)

Oliver Stein

00:52:05

Mixed-Integer Optimization II, Section 3.3.3 (The nonconvex case)

Mixed-Integer Optimization II, Section 3.3.3 (The nonconvex case)

Oliver Stein

00:23:11

Mixed-Integer Optimization II, Section 3.4.1 (Reduced feasible set and reduced objective function)

Mixed-Integer Optimization II, Section 3.4.1 (Reduced feasible set and reduced objective function)

Oliver Stein

00:59:07

Mixed-Integer Optimization II, Section 3.3.1 (B&B für MINLP - A conceptual algorithm), Section 3.3.2 (The convex case)

Mixed-Integer Optimization II, Section 3.3.1 (B&B für MINLP - A conceptual algorithm), Section 3.3.2 (The convex case)

Oliver Stein

00:39:49

Mixed-Integer Optimization II, Section 3.4.2 (Convexity of the reduced feasible set and of the reduced objective function)

Mixed-Integer Optimization II, Section 3.4.2 (Convexity of the reduced feasible set and of the reduced objective function)

Oliver Stein

00:37:28

Mixed-Integer Optimization II, Section 3.4.5 (Optimality cuts), part 1

Mixed-Integer Optimization II, Section 3.4.5 (Optimality cuts), part 1

Oliver Stein

00:17:55

Mixed-Integer Optimization II, Section 3 (Mixed-integer nonlinear optimization), Introduction

Mixed-Integer Optimization II, Section 3 (Mixed-integer nonlinear optimization), Introduction

Oliver Stein

00:38:25

Mixed-Integer Optimization II, Section 3.1 (Models in portfolio optimization)

Mixed-Integer Optimization II, Section 3.1 (Models in portfolio optimization)

Oliver Stein

01:57:42

Nature-inspired optimization methods SS 2022 : Chapter: Evolutionary algorithms

Nature-inspired optimization methods SS 2022 : Chapter: Evolutionary algorithms

Pradyumn Shukla

01:00:22

Nature-inspired optimization methods SS 2022 : Chapter: An Algorithmic Framework for Many-Objective-Optimization

Nature-inspired optimization methods SS 2022 : Chapter: An Algorithmic Framework for Many-Objective-Optimization

Pradyumn Shukla

01:44:35

Nature-inspired optimization methods SS 2022 : Modelling fairness in resource allocation problems

Nature-inspired optimization methods SS 2022 : Modelling fairness in resource allocation problems

Pradyumn Shukla

01:02:19

Nature-inspired optimization methods SS 2022 : Chapter: Constraint handling techniques

Nature-inspired optimization methods SS 2022 : Chapter: Constraint handling techniques

Pradyumn Shukla

01:03:54

Nature-inspired optimization methods SS 2022 : User preferences, distributed computing

Nature-inspired optimization methods SS 2022 : User preferences, distributed computing

Pradyumn Shukla

02:11:17

Nature-inspired optimization methods SS 2022 : Multi-objective Evolutionary Algorithms

Nature-inspired optimization methods SS 2022 : Multi-objective Evolutionary Algorithms

Pradyumn Shukla

01:13:17

Nature-inspired optimization methods SS 2022 : Robust Design Optimization

Nature-inspired optimization methods SS 2022 : Robust Design Optimization

Pradyumn Shukla

01:20:15

Nature-inspired optimization methods SS 2022 : Search operators

Nature-inspired optimization methods SS 2022 : Search operators

Pradyumn Shukla

01:37:02

Nature-inspired optimization methods SS 2022 : Chapter: Representation

Nature-inspired optimization methods SS 2022 : Chapter: Representation

Pradyumn Shukla

01:01:02

Nature-inspired optimization methods SS 2022 : Problem Solving and Basic Concepts II. Basic Concepts

Nature-inspired optimization methods SS 2022 : Problem Solving and Basic Concepts II. Basic Concepts

Pradyumn Shukla

01:30:07

Nature-inspired optimization methods SS 2022 : Chapter: Escaping Local Minima

Nature-inspired optimization methods SS 2022 : Chapter: Escaping Local Minima

Pradyumn Shukla

01:22:07

Nature-inspired optimization methods SS 2022 : Chapter 1: Problem Solving and Basic Concepts

Nature-inspired optimization methods SS 2022 : Chapter 1: Problem Solving and Basic Concepts

Pradyumn Shukla

01:41:21

Nature-inspired optimization methods SS 2022 : Chapter: Escaping Local Minima II. Tabu Search

Nature-inspired optimization methods SS 2022 : Chapter: Escaping Local Minima II. Tabu Search

Pradyumn Shukla

00:24:42

Nature-inspired optimization methods SS 2022 : Introductory lecture

Nature-inspired optimization methods SS 2022 : Introductory lecture

Pradyumn Shukla

01:06:05

Seminar on IPCC Assessment Report

Seminar on IPCC Assessment Report

Joaquim Pinto, Patrick Ludwig

01:10:15

Climate Modelling and Dynamics with ICON

Climate Modelling and Dynamics with ICON

Joaquim G. Pinto, Patrick Ludwig, Aiko Voigt

00:40:21

Global Optimization I, Section 2.8.5 (Frank-Wolfe method), part 1

Global Optimization I, Section 2.8.5 (Frank-Wolfe method), part 1

Oliver Stein

00:32:15

Global Optimization I, Section 1.2.1 (Definition of solvability)

Global Optimization I, Section 1.2.1 (Definition of solvability)

Oliver Stein

00:20:20

Global Optimization I, Section 2.7.1 (Lagrange- and Wolfe-duality), part 3

Global Optimization I, Section 2.7.1 (Lagrange- and Wolfe-duality), part 3

Oliver Stein

00:34:43

Global Optimization I, Section 1.2.4 (Unbounded feasible sets), part 2

Global Optimization I, Section 1.2.4 (Unbounded feasible sets), part 2

Oliver Stein

00:58:05

Parametric Optimization, Section 1.1 (Shadow prices and three key questions), Section 1.2 (Hotelling's lemma and the same questions)

Parametric Optimization, Section 1.1 (Shadow prices and three key questions), Section 1.2 (Hotelling's lemma and the same questions)

Oliver Stein

01:00:14

Parametric Optimization, Section 1.3 (Algorithms and a fourth key question), Section 1.4 (Decomposition methods), Section 1.5 (Robust and semi-infinite optimization)

Parametric Optimization, Section 1.3 (Algorithms and a fourth key question), Section 1.4 (Decomposition methods), Section 1.5 (Robust and semi-infinite optimization)

Oliver Stein

00:55:20

Global Optimization I, Section 2.1 (Convexity), part 2

Global Optimization I, Section 2.1 (Convexity), part 2

Oliver Stein

00:51:34

Parametric Optimization, Section 2.2.3 (Quadratic indices), Section 2.2.4 (Stability of nondegenerate minimal points)

Parametric Optimization, Section 2.2.3 (Quadratic indices), Section 2.2.4 (Stability of nondegenerate minimal points)

Oliver Stein

00:29:18

Parametric Optimization, Section 2.3.7 (Sensitivity of nondegenerate minimal values), part 1

Parametric Optimization, Section 2.3.7 (Sensitivity of nondegenerate minimal values), part 1

Oliver Stein

00:22:20

Parametric Optimization, Section 2.3.1 (Criticality notions for constrained problems)

Parametric Optimization, Section 2.3.1 (Criticality notions for constrained problems)

Oliver Stein

00:45:58

Parametric Optimization, Section 2.3.5 (Stability of nondegenerate minimal points)

Parametric Optimization, Section 2.3.5 (Stability of nondegenerate minimal points)

Oliver Stein

01:22:49

Parametric Optimization, Section 2.3.2 (Three regularity conditions)

Parametric Optimization, Section 2.3.2 (Three regularity conditions)

Oliver Stein

00:19:39

Parametric Optimization, Section 4.1.4 (Reduction Ansatz)

Parametric Optimization, Section 4.1.4 (Reduction Ansatz)

Oliver Stein

00:48:13

Parametric Optimization, Section 1.9 (Counter examples)

Parametric Optimization, Section 1.9 (Counter examples)

Oliver Stein

00:19:46

Global Optimization I, Section 2.8.4 (Kelley's cutting plane method), part 2

Global Optimization I, Section 2.8.4 (Kelley's cutting plane method), part 2

Oliver Stein

00:25:56

Global Optimization I, Section 2.7.2 (The KKT conditions)

Global Optimization I, Section 2.7.2 (The KKT conditions)

Oliver Stein

00:29:26

Global Optimization I, Section 2.8.5 (Frank-Wolfe method), part 2

Global Optimization I, Section 2.8.5 (Frank-Wolfe method), part 2

Oliver Stein

00:17:44

Global Optimization I, Section 2.8.5 (Frank-Wolfe method), part 3

Global Optimization I, Section 2.8.5 (Frank-Wolfe method), part 3

Oliver Stein

00:39:21

Parametric Optimization, Section 3.2.2 (Applications and characterizations for semicontinuity properties of functions)

Parametric Optimization, Section 3.2.2 (Applications and characterizations for semicontinuity properties of functions)

Oliver Stein

00:25:07

Parametric Optimization, Section 2.3.7 (Sensitivity of nondegenerate minimal values), part 2

Parametric Optimization, Section 2.3.7 (Sensitivity of nondegenerate minimal values), part 2

Oliver Stein

00:33:58

Parametric Optimization

Parametric Optimization

Oliver Stein

00:32:46

Parametric Optimization, Section 3.7 (Directional sensitivity of minimal values)

Parametric Optimization, Section 3.7 (Directional sensitivity of minimal values)

Oliver Stein

01:21:10

Global Optimization I, Section 2.7.1 (Lagrange- and Wolfe-duality), part 2

Global Optimization I, Section 2.7.1 (Lagrange- and Wolfe-duality), part 2

Oliver Stein

00:44:35

Global Optimization I, Section 2.2.1 (Higher-dimensional first derivatives)

Global Optimization I, Section 2.2.1 (Higher-dimensional first derivatives)

Oliver Stein

00:32:10

Parametric Optimization, Section 4.1.3 (Optimality conditions)

Parametric Optimization, Section 4.1.3 (Optimality conditions)

Oliver Stein

01:04:25

Global Optimization I, Section 2.8.4 (Kelley's cutting plane method), part 1

Global Optimization I, Section 2.8.4 (Kelley's cutting plane method), part 1

Oliver Stein

00:31:03

Global Optimization I, Section 2.8 (Numerical methods); Section 2.8.1 (Basic idea of the gradient method)

Global Optimization I, Section 2.8 (Numerical methods); Section 2.8.1 (Basic idea of the gradient method)

Oliver Stein

00:51:26

Global Optimization I, Section 2.5.1 (Higher-dimensional second derivatives)

Global Optimization I, Section 2.5.1 (Higher-dimensional second derivatives)

Oliver Stein

00:40:30

Global Optimization I, Section 2.3 (Solvability of convex optimization problems)

Global Optimization I, Section 2.3 (Solvability of convex optimization problems)

Oliver Stein

00:23:10

Global Optimization I, Section 2.8.3 (Basic idea of cutting plane methods)

Global Optimization I, Section 2.8.3 (Basic idea of cutting plane methods)

Oliver Stein

00:16:52

Parametric Optimization, Section 2.3.6 (Sensitivity of nondegenerate minimal points)

Parametric Optimization, Section 2.3.6 (Sensitivity of nondegenerate minimal points)

Oliver Stein

00:42:19

Parametric Optimization, Section 3.4 (Continuity properties of the feasible set mapping)

Parametric Optimization, Section 3.4 (Continuity properties of the feasible set mapping)

Oliver Stein

00:28:15

Parametric Optimization, Section 3.5 (Continuity properties of constrained minimal values), Section 3.6 (Continuity properties of constrained minimal points)

Parametric Optimization, Section 3.5 (Continuity properties of constrained minimal values), Section 3.6 (Continuity properties of constrained minimal points)

Oliver Stein

00:42:08

Global Optimization I, Section 1.1 (Examples and notions), part 2

Global Optimization I, Section 1.1 (Examples and notions), part 2

Oliver Stein

00:52:35

Global Optimization I, Section 1.1 (Examples and notions), part 3

Global Optimization I, Section 1.1 (Examples and notions), part 3

Oliver Stein

00:49:42

Global Optimization I, Section 1.1 (Examples and notions), part 1

Global Optimization I, Section 1.1 (Examples and notions), part 1

Oliver Stein

00:52:11

Global Optimization I, Section 1.2.2 (Types of unsolvability)

Global Optimization I, Section 1.2.2 (Types of unsolvability)

Oliver Stein

00:35:04

Global Optimization I, Section 1.2.3 (Weierstrass theorem)

Global Optimization I, Section 1.2.3 (Weierstrass theorem)

Oliver Stein

00:09:54

Parametric Optimization, Introduction

Parametric Optimization, Introduction

Oliver Stein

00:49:46

Global Optimization I, Section 2.7 (Optimality conditions for constrained convex problems); Section 2.7.1 (Lagrange- and Wolfe-duality), part 1

Global Optimization I, Section 2.7 (Optimality conditions for constrained convex problems); Section 2.7.1 (Lagrange- and Wolfe-duality), part 1

Oliver Stein

00:38:17

Global Optimization I, Section 2.8.2 (Basic idea of Newton's method)

Global Optimization I, Section 2.8.2 (Basic idea of Newton's method)

Oliver Stein

01:02:20

Global Optimization I, Section 1.2.4 (Unbounded feasible sets), part 1

Global Optimization I, Section 1.2.4 (Unbounded feasible sets), part 1

Oliver Stein

00:47:05

Global Optimization I, Section 2.1 (Convexity), part 1

Global Optimization I, Section 2.1 (Convexity), part 1

Oliver Stein

00:34:19

Global Optimization I, Section 2.2.2 (C1-characterization)

Global Optimization I, Section 2.2.2 (C1-characterization)

Oliver Stein

00:33:32

Parametric Optimization, Section 3.1 (Preliminary thoughts)

Parametric Optimization, Section 3.1 (Preliminary thoughts)

Oliver Stein

00:08:47

Global Optimization I, Section 2.6 (Monotonicity characterization of convexity)

Global Optimization I, Section 2.6 (Monotonicity characterization of convexity)

Oliver Stein

00:24:16

Parametric Optimization, Section 2.3.3 (Nondegenerate critical points), Section 2.3.4 (Linear and quadratic indices)

Parametric Optimization, Section 2.3.3 (Nondegenerate critical points), Section 2.3.4 (Linear and quadratic indices)

Oliver Stein

00:44:33

Parametric Optimization, Section 1.6 (Bilevel optimization), Section 1.7 (Nash games), Section 1.8 (Multiobjective optimization)

Parametric Optimization, Section 1.6 (Bilevel optimization), Section 1.7 (Nash games), Section 1.8 (Multiobjective optimization)

Oliver Stein

00:44:38

Global Optimization I, Section 2.4 (Optimality conditions for unconstrained convex problems)

Global Optimization I, Section 2.4 (Optimality conditions for unconstrained convex problems)

Oliver Stein

00:24:21

Parametric Optimization, Section 2.2.5 (Sensitivity of nondegenerate minimal points)

Parametric Optimization, Section 2.2.5 (Sensitivity of nondegenerate minimal points)

Oliver Stein

00:32:36

Parametric Optimization, Section 3.2.1 (Semicontinuity of functions)

Parametric Optimization, Section 3.2.1 (Semicontinuity of functions)

Oliver Stein

00:24:06

Parametric Optimization, Section 3.2.4 (Lower semicontinuity of minimal values), part 3

Parametric Optimization, Section 3.2.4 (Lower semicontinuity of minimal values), part 3

Oliver Stein

00:45:17

Parametric Optimization, Section 3.3.1 (Basic concepts for setvalued mappings)

Parametric Optimization, Section 3.3.1 (Basic concepts for setvalued mappings)

Oliver Stein

00:22:23

Parametric Optimization, Section 3.3.2 (Closedness and local boundedness of unconstrained minimal points)

Parametric Optimization, Section 3.3.2 (Closedness and local boundedness of unconstrained minimal points)

Oliver Stein

00:20:30

Global Optimization I, Section 2.7.3 (Complementarity)

Global Optimization I, Section 2.7.3 (Complementarity)

Oliver Stein

00:27:05

Mixed-Integer Optimization I, Section 2 (Mixed-integer linear optimization), Introduction

Mixed-Integer Optimization I, Section 2 (Mixed-integer linear optimization), Introduction

Oliver Stein