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Optimization and Simulation
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Related lectures (60)
Monte Carlo Moves in Simulation
Explores Monte Carlo moves in simulation, including trial moves and biased moves, comparing Monte Carlo with Molecular Dynamics.
Energy Systems Simulation and Optimization
By Prof. François Marechal covers the simulation and optimization of energy systems in industrial processes, waste, resources, and energy conversion.
Optimization and Simulation
Introduces discrete event simulation through the example of Rico at Satellite, emphasizing the importance of statistical analysis.
Optimization and Simulation
Explores optimization and simulation techniques for variance reduction in draws.
Hydrologic Parameters Optimization
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Covers hydrologic parameters optimization using RS MINERVE software and analyzes the best solution.
Applied Mechanical Design: Detail Design
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Explores the process of detail design in mechanical engineering, from concept to final design.
Optimization vs. Simulation in Energy Systems Engineering
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Discusses optimization vs. simulation in energy systems engineering, district heating networks, and scientific writing guidelines.
Monte Carlo Chain: Motivation and Algorithm
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Explores the motivation and algorithm behind the Monte Carlo Chain method.
Introduction to Optimization and Operations Research
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Covers fundamental concepts of optimization and operations research, exploring real-world examples and key topics over a semester.
Connect Four: Alpha-Beta Pruning and Monte-Carlo Tree Search
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Explores solving Connect Four using game theory algorithms and compares Alpha-Beta pruning with Monte-Carlo tree search.
Connect Four: Alpha-Beta Pruning and Monte-Carlo Tree Search
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Explores solving Connect Four using game theory and algorithms for optimal strategy in minimum time.
Optimization in Large Search Spaces: GPU-Accelerated Join Order
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Explores GPU-accelerated join order optimization in large search spaces, leveraging graph topology to reduce computational overheads.
Stochastic Gradient Descent
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Explores stochastic gradient descent optimization and the Mean-Field Method in neural networks.
Inference of Effects: Models and Interactions
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Discusses constant and random coefficient models, factors optimization, and interactions estimation in performance analysis.
Quantifying Myelin Water Exchange: Two-Pool Model and bSSFP Imaging
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Explores quantifying myelin water exchange using a two-pool model and bSSFP imaging for precise estimation in white matter.
Proof of Strong Duality
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Covers the proof of strong duality in optimization problems and provides examples of Rayleigh quotient optimization.
Neurobiological Signal Processing
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Explores neurobiological signal processing, covering spike modeling, signal classification, and data characterization using principal component analysis.
Data Cleaning Challenges: Optimizing Error Detection
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Addresses challenges in data cleaning for analysis, proposing optimizations to reduce processing time.
Gradient Descent: Optimization and Constraints
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Discusses gradient descent for optimization with equality constraints and iterative convergence criteria.
Debugging and Optimization
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Covers types of errors in programming and emphasizes the importance of debugging and optimization techniques.
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