Lectures related to Data Reconciliation and Parameter Identification

Optimization with Constraints: KKT Conditions

Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.

Optimization Methods: Theory Discussion

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Degree of Freedom Analysis

Explores degree of freedom analysis, redundancy, and data reconciliation in process modeling and optimization.

Energy Systems Optimization

Explores energy systems modeling, optimization, and cost analysis for efficient operations.

Optimizing Recursive Queries

Explores optimizing recursive queries in database systems using Datalog and semirings, discussing the challenges and solutions in data analytics.

Optimisation Strategies: Energy Systems Modelling and Optimization

Explores solving strategies for energy system optimization problems and different types of optimization approaches.

Energy System Modeling: Optimization and Performance Indicators

Explores energy system modeling using optimization techniques and performance indicators.

Code Optimization: Speeding-up Analyses

Explores techniques to speed up dataflow analyses and discusses the importance of node ordering and post-order traversal.

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.

Optimization Methods

Covers the Newton's local method in Python using NumPy for optimization.

Electroacoustic Absorbers: Performance Evaluation and Conclusions

Explores the performance evaluation and conclusions of electroacoustic absorbers in room modal equalization and optimization.

Sterotomie: Mono Panel

Explores the geometric design and machining preparation of a mono panel.

Single Inequality or Equality Constraint

Covers single inequality or equality constraints and necessary optimality conditions in optimization problems.

Geometric Computing Laboratory: Inverse Design Optimization

Explores inverse design optimization in geometric computing, covering topics such as deployable structures, material-aware design, and programmed materials.

Spark DataFrames: Basics and Optimization

Covers the basics of Spark DataFrames, their advantages, performance comparison with RDDs, and practical demos.

Optimization methods

Covers optimization methods, focusing on gradient methods and line search techniques.

Relaxation-based Retiming

Covers relaxation-based retiming to optimize cycle-time by shortening paths with excessive delays.

Optimization and Simulation

Covers optimization and simulation techniques for drawing from multivariate distributions and dealing with correlations.

Semi-Definite Programming

Covers semi-definite programming and optimization over positive semidefinite cones.