Questions tagged [loss]

For questions related to the concept of loss (or cost) in machine learning or other AI sub-fields.

19 questions with no upvoted or accepted answers
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How to perform back-propagation in Decoupled Neural Interfaces?

I am attempting to create a fully decoupled feed-forward neural network by using decoupled neural interfaces (DNIs) as explained in the paper Decoupled Neural Interfaces using Synthetic Gradients (...
2
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1answer
34 views

Data scan not making sense for coco dataset

I am doing a simple scan to see how dataset size affects training. Basically, I took 10% of the coco dataset and trained a yolov3 net (from scratch) to just look for people. Then I took 20% of the ...
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0answers
19 views

Why is the loss of one of the outputs of a model with multiple outputs increasing while the others are decreasing?

I'm a newbie in neural networks. I'm trying to fit my neural network that has 3 different outputs: semantic segmentation, box mask and box coordinates. When my model is training, the loss of ...
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32 views

Could the inputs of the mean squared-error loss function be transformed to allow larger learning rates?

In the context of a neural network $\hat{y} = f_\theta(\mathbf{x})$ with parameters $\theta$ that is trained to perform regression such that the prediction $\hat{\mathbf{y}} = [\hat{y}_1,\hat{y}_2,...,...
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0answers
10 views

How does the loss landscape look like or change when a model is overfitting?

My understanding is that when a model starts overfitting, it no longer learns useful features and starts remembering the training data set. Given enough epochs and sufficient parameters, a model can ...
1
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1answer
63 views

Can someone explain me what does this loss curve says?

I was training a CNN model on TensorFlow. After a while I came back and saw this loss curve: The green curve is training loss and the gray one is validation loss. I know that before epoch 394 the ...
1
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0answers
30 views

WGAN-GP Loss formalization

I have to write the formalization of the loss function of my network, built following the WGAN-GP model. The discriminator takes 3 consecutive images as input (such as 3 consecutive frames of a video) ...
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0answers
36 views

Why does loss and accuracy for a multi label classification ann does not change overtime?

I have run into a strange behavior of my multi label classification ANN ...
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0answers
63 views

LSTM - MAPE Loss Function gives Better Results when Data is De-Scaled before Loss Calculation

I am building an LSTM for predicting a price chart. MAPE resulted in the best loss function compared to ...
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0answers
226 views

what will be the best loss function for unet to predict the each pixel values?

I'm predicting the used 9 pictures to predict the last picture so (40,40,9) -> unet -> (40,40,1) but as you see the predict picture It's not just a mask(0or 1) its float so which loss function ...
1
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1answer
79 views

Do smaller loss values during DQN training produce better policies?

During the training of DQN, I noticed that the model with prioritized experience replay (PER) had a smaller loss in general compared to a DQN without PER. The mean squared loss was an order of ...
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0answers
48 views

How MSE should be appliead with multi target deep network?

I'm having a problem understanding how the MSE should be used when working with a multidimensional target, e.g 3 dimensiones. (My outputs are continuois values, not categorical) Let us say I have a ...
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0answers
28 views

Crossing of training and validation loss

During training of my models I often encounter the following situation about training (green) and validation (gray) loss: Initially, the validation loss is significantly lower than the training loss. ...
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0answers
31 views

Deduce properties of the loss functions from the training loss curves

I have two convex, smooth loss functions to minimise. During the training (a very simple model) using batch SGD (with tuned optimal learning rate for each loss function), I observe that the (log) loss ...
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22 views

Incorporating regularization for the kernel perceptron

To my understanding, the following is how the kernel perceptron works.    Kernel perceptron algorithm       The parameters to be calculated are $\alpha = \begin{pmatrix} \alpha_1 &\ldots &\...
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16 views

Loss function for better class separability in multi class classification

So I am trying to enforce better separability in my deep learning model and was wondering what I can use besides cross entropy loss to do that? Could maybe using logarithm with different basis in ...
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0answers
44 views

Variance of the Gaussian policy is not decreasing while training the agent using Soft Actor-Critic method

I've written my own version of SAC(v2) for a problem with continuous action space. While training, the losses for the value network and both q functions steadily decrease down to 0.02-0.03. The loss ...
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0answers
44 views

Non-trainable regularizer in loss function

I train a fully convoluted network for semantic segmentation. To each convolution blocks, I associate a module pruning feature maps to reduce the quantity of information generated by the network. From ...
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0answers
50 views

VAE KL divergence loss decreases really fast

I am new to training VAEs and I am using it on some 16x16 images, that contains some images from a physics experiment with one or 2 events i.e. the images are mainly black, except for one or 2 regions ...