Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Descent methods and line search: Validity of the Wolfe conditions
Graph Chatbot
Related lectures (50)
Energy Systems Optimization
Explores energy systems modeling, optimization, and cost analysis for efficient operations.
Optimization with Constraints: KKT Conditions
Covers the optimization with constraints, focusing on the Karush-Kuhn-Tucker (KKT) conditions.
Energy optimization strategies
Covers brainstorming options for smart operation changes, heat recovery, and PV panel performance.
Optimisation Strategies: Energy Systems Modelling and Optimization
Explores solving strategies for energy system optimization problems and different types of optimization approaches.
Electroacoustic Absorbers: Performance Evaluation and Conclusions
Explores the performance evaluation and conclusions of electroacoustic absorbers in room modal equalization and optimization.
Energy System Modeling: Optimization and Performance Indicators
Explores energy system modeling using optimization techniques and performance indicators.
Optimization and Simulation
Covers optimization and simulation techniques for drawing from multivariate distributions and dealing with correlations.
Optimization methods
Covers optimization methods, focusing on gradient methods and line search techniques.
Optimization Methods
MOOC: Optimization: principles and algorithms - Network and discrete optimization
MOOC: Optimization: principles and algorithms - Unconstrained nonlinear optimization
MOOC: Optimization: principles and algorithms - Linear optimization
Covers the Newton's local method in Python using NumPy for optimization.
MILP Model and Typical Days by FM
Discusses MILP model, typical days, clustering, and extreme periods analysis in energy systems optimization.
Computer Architecture: Algorithms to Programs (Compilation)
Explores the transition from algorithms to programs through compilation, emphasizing constraints and machine-understandable coding practices.
Linear Optimization: Directional Derivatives
Explores directional derivatives in linear optimization and their impact on objective functions.
Recommender Systems: Matrix Factorization
Explores matrix factorization in recommender systems, covering optimization, evaluation metrics, and challenges in scaling.
Predicting Completion Time: Optimization Strategies
Discusses predicting completion time and optimizing activities through efficient orchestration strategies and experiment-based completion curve predictions.
Simplex Algorithm: Initial Tableau & General Case
MOOC: Optimization: principles and algorithms - Linear optimization
Covers the simplex algorithm, from initial tableau to general case.
Set Cover: Integrality Gap
Explores the integrality gap concept in set cover and multiplicative weights algorithms.
Degree of Freedom Analysis
Explores degree of freedom analysis, redundancy, and data reconciliation in process modeling and optimization.
Optimization and Simulation
Covers the general framework of optimization and simulation, including deterministic control and the optimization problem.
Optimization algorithms
Log in to Mediaspace to watch this video
Covers optimization algorithms, focusing on Proximal Gradient Descent and its variations.
Single Inequality or Equality Constraint
Log in to Mediaspace to watch this video
Covers single inequality or equality constraints and necessary optimality conditions in optimization problems.
Previous
Page 1 of 3
Next
