How can I avoid local minima in optimization problems?

How can I avoid local minima in optimization problems?

To avoid local minima, you can use techniques like simulated annealing, genetic algorithms, or momentum-based methods.

What is simulated annealing and how does it help?

Simulated annealing is a probabilistic technique that explores the solution space and can escape local minima by allowing uphill moves.

Are there any specific algorithms that are better for this?

Yes, algorithms like Adam, RMSprop, and stochastic gradient descent with restarts are effective in avoiding local minima.

Can you explain how momentum-based methods work?

Momentum-based methods accelerate gradients vectors in the right directions, thus helping to navigate past local minima.