Nov 1, 2018 · When I trained one of the torch vision architectures on my dataset without using class weights or balanced sampling, the model quickly finds that if it always predicts common …

Oct 12, 2021 · Iterated Local Search is a stochastic global optimization algorithm. It involves the repeated application of a local search algorithm to modified versions of a good solution found …

Dec 1, 2021 · Sometimes it gets stuck in local optima. I have implemented the algorithm using the TD-0 advantage i.e. Here is my code: N = n. kernel = np.ones(N) conv_len = x.shape[0]-N. y = …

Jun 20, 2023 · The accumulated momentum helps the algorithm overcome small local minima and reach the global minimum faster. The example code snippet in Python using TensorFlow:

Jan 9, 2025 · Optimization Algorithm: An algorithm (like Gradient Descent or its variants) that iteratively updates the parameters to find the minimum of the cost function. Local Minimum: A …

Sep 20, 2023 · What I would try first is replace the dataset with just two batches. Does the model successfully learn them? (and not return a constant)? Also, I would keep printing the MSE and …

I am using ppo to try to learn breakout, but the agent is stuck in a local optima where the agent waits in a corner cause most of the time the ball after spawning moves towards the corner...

This tutorial shows how to perform cross-validation of the model: https://botorch.org/tutorials/batch_mode_cross_validation - You should be able to adapt this to …

Aug 15, 2024 · So I'm led to believe the model is trapped in a local optima. But I don't know exactly why, since the MSE version of this code easily works (I tested it with the exact same …

r the operations you’re performing. If you do want to do computations with PyTorch tensors rather than numpy, wrap them in with torch.no_grad() to tell PyTorch that this is ‘dead end’ code and …