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01:02:18
Nature-inspired optimization methods SS 2023, Teil 14
Nature-inspired optimization methods SS 2023, Teil 14
Pradyumn Shukla
01:03:54
Nature-inspired optimization methods SS 2023, Teil 15
Nature-inspired optimization methods SS 2023, Teil 15
Pradyumn Shukla
01:13:17
Nature-inspired optimization methods SS 2023, Teil 16
Nature-inspired optimization methods SS 2023, Teil 16
Pradyumn Shukla
00:59:35
Nature-inspired optimization methods SS 2023, Teil 10
Nature-inspired optimization methods SS 2023, Teil 10
Pradyumn Shukla
00:48:18
Nature-inspired optimization methods SS 2023, Teil 11
Nature-inspired optimization methods SS 2023, Teil 11
Pradyumn Shukla
00:23:24
Nature-inspired optimization methods SS 2023, Teil 12
Nature-inspired optimization methods SS 2023, Teil 12
Pradyumn Shukla
01:00:22
Nature-inspired optimization methods SS 2023, Teil 13
Nature-inspired optimization methods SS 2023, Teil 13
Pradyumn Shukla
01:20:15
Nature-inspired optimization methods SS 2023, Teil 9
Nature-inspired optimization methods SS 2023, Teil 9
Pradyumn Shukla
01:57:42
Nature-inspired optimization methods SS 2023, Teil 8
Nature-inspired optimization methods SS 2023, Teil 8
Pradyumn Shukla
01:32:47
Nature-inspired optimization methods SS 2023, Teil 7
Nature-inspired optimization methods SS 2023, Teil 7
Pradyumn Shukla
01:30:07
Nature-inspired optimization methods SS 2023, Teil 6
Nature-inspired optimization methods SS 2023, Teil 6
Pradyumn Shukla
01:37:02
Nature-inspired optimization methods SS 2023, Teil 4
Nature-inspired optimization methods SS 2023, Teil 4
Pradyumn Shukla
01:41:21
Nature-inspired optimization methods SS 2023, Teil 5
Nature-inspired optimization methods SS 2023, Teil 5
Pradyumn Shukla
01:01:02
Nature-inspired optimization methods SS 2023, Teil 3
Nature-inspired optimization methods SS 2023, Teil 3
Pradyumn Shukla
00:19:02
Nature-inspired optimization methods SS 2023, Teil 1
Nature-inspired optimization methods SS 2023, Teil 1
Pradyumn Shukla
01:21:39
Nature-inspired optimization methods SS 2023, Teil 2
Nature-inspired optimization methods SS 2023, Teil 2
Pradyumn Shukla
00:30:02
Computational Economics WS 2022/23, Teil 12
Computational Economics WS 2022/23, Teil 12
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