All Questions
Tagged with deep-learningobjective-functions
59 questions
0votes
0answers
38views
how to use contrastive loss function for multi label classification?
I have a multi label classification problem, where I was initially using a binary cross entropy loss and my labels are one hot encoded. I found a paper similar to my application and have used ...
- 41
1vote
1answer
38views
How can gradient descent optimize a loss surface that's never fully computed?
In gradient descent for neural networks, we optimize over a loss surface defined by our loss function L(W) where W represents the network weights. However, since there are infinitely many possible ...
0votes
0answers
55views
Loss function on intermediate layers of the networks
Typically in supervised learning, a neural networks' output is compared to the targets through a loss function, and the gradients are backpropagated. Is it a bad idea to also have a loss function on ...
- 11
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0answers
15views
Application thats compatible with android that allows you to access the wifi signals around you and constructs its own
Can we develop a application thats compatible with android that allows you to access the wifi signals around you and constructs its own? By continuously encryption data by the wifi signal by ...
0votes
1answer
103views
Using conditional probability as an estimate in a loss function
I have a rather large ML framework that takes multiple conditional probability terms that are computed via classifiers/neural networks. This arbitrary loss function is computed via a function: ...
- 101
1vote
2answers
71views
How do I assign a weight to an additional loss?
I am trying to do multi-spectral image fusion. I am using the following paper as a reference. https://arxiv.org/pdf/1804.08361.pdf The code available on GitHub works well. But, I am trying to add some ...
0votes
1answer
473views
What is the correct loss function for binary classification: Cross entropy or Binary cross entropy?
Let's say I have a binary classification problem and I want to solve it by means of FC neural net. So which approach will be correct: 1) define the last layer of NN like this ...
- 23
0votes
1answer
4kviews
What's the difference between classification and segmentation in deep learning?
What's the difference between classification and segmentation in deep learning? In particular, can the classification loss function be used for segmentation problems?
1vote
1answer
749views
Why MSE and MAE yield poor results when used with gradient-based optimization for classification?
Deep learning book chapter 6: In 6.2.1.2 last paragraph: Unfortunately, mean squared error and mean absolute error often lead to poor results when used with gradient-based optimization. Some output ...
0votes
1answer
68views
Learning curve converges with huge errors
I am training an auto-encoder over $10^4$ epochs. I get a converging learning curve. However the error at the last stages stays huge $\sim10^{15}$. What does this mean? does it mean that my auto-...
- 101
1vote
0answers
49views
Learning values in open ball: which final layers to employ?
I'm fairly new to deep learning and looking for some reference literature... Specifically, I want to train a neural network to predict vectors $v \in \mathbb{R}^3$ under the constraint $||v||\leq 1$. ...
- 111
2votes
1answer
2kviews
What is the reason we loop over epochs when training a neural network?
After reading through this thread and some other resources online, I still do not understand the role of epochs in training a neural network. I understand that one epoch is one iteration through the ...
- 92
1vote
0answers
95views
a loss for binary step function data
I have some data with ground truth that looks like a binary step function, where part of it is 0 and part is one. An example for the GT can be like ...
- 111
1vote
0answers
86views
Where do the objective functions proposed in this paper by Carlini-Wagner attack come from?
I'm trying to understand the paper by Carlini and Wagner on deep neural networks adversarial attacks. On page 44, in Section V-A, it is explained how the loss function to the described problem was ...
- 111
2votes
0answers
59views
Can a GIoU loss (generalized intersection over union) be used after an STN module (spatial transformer network)?
I have a model that uses an STN module for number detection and Mean Squared Error loss. But I would like to replace it for GIoU, because MSE doesn't take into account how much of the target area has ...
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