- #1
luxxio
- 44
- 0
I need to optimize a maximum likelihood function with many many variables (~10^2 variables). what is the faster method?
thanx
thanx
The best method for a many many variable optimization problem?
- Thread starter luxxio
- Start date
-
- Tags
- Method Optimization Variable
Click For Summary
SUMMARY
The discussion focuses on optimizing a maximum likelihood function with approximately 100 variables. Key considerations include the nature of the function—whether it is convex or quadratic—and the types of constraints involved, such as equality or inequality constraints, and whether they are linear. The optimization method chosen will depend heavily on these characteristics.
PREREQUISITES- Understanding of maximum likelihood estimation
- Familiarity with convex and quadratic functions
- Knowledge of linear and nonlinear constraints
- Experience with optimization algorithms
- Research optimization algorithms suitable for convex functions
- Learn about methods for handling constraints in optimization problems
- Explore software tools for maximum likelihood estimation, such as R or Python's SciPy
- Study the implications of variable scaling in high-dimensional optimization
Data scientists, statisticians, and machine learning practitioners involved in complex optimization problems, particularly those dealing with high-dimensional data and constraints.
Similar threads
- · Replies 5 ·
- · Replies 1 ·
- · Replies 2 ·
- · Replies 17 ·
- · Replies 4 ·
- · Replies 3 ·
- · Replies 5 ·
- · Replies 12 ·
- · Replies 1 ·
High School
Binary variables (Absolute values)
- · Replies 2 ·