Unanswered Questions
91 questions with no upvoted or accepted answers
8
votes
2
answers
974
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How should we interpret this figure that relates the perceptron criterion and the hinge loss?
I am currently studying the textbook Neural Networks and Deep Learning by Charu C. Aggarwal. Chapter 1.2.1.2 Relationship with Support Vector Machines says the following:
The perceptron criterion is ...
CommunityBot
- 1
5
votes
1
answer
2k
views
Which other loss functions for hierarchical multi-label classification could I use?
I am looking to try different loss functions for a hierarchical multi-label classification problem. So far, I have been training different models or submodels like multilayer perceptron (MLP) branch ...
CommunityBot
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4
votes
0
answers
40
views
How do weights changes handles during back-propagation when there are unknown labels
I have a question about how weights are updated during back-propagation for some of my samples that have unknown labels (please note, unknown, not missing). The reason they are unknown is because this ...
- 171
3
votes
0
answers
431
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Loss function to minimize the distance between sets
Are there references or links to examples about loss functions "Distance Metrics" which could be used to minimize the distance between two sets for a neural network. More precisely, this ...
- 131
3
votes
0
answers
83
views
Enforcing sparsity constraints that make use of spatial contiguity
I have a deep learning network that outputs grayscale image reconstructions. In addition to good reconstruction performance (measured through mean squared error or some other measure like psnr), I ...
- 143
3
votes
0
answers
92
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Why is the loss associated with my neural network increasing?
I am currently learning neural networks using data from Touchscreen Input as a Behavioral Biometric. Basically, I am trying to predict "User ID" by training the neural network model shown ...
- 181
3
votes
0
answers
1k
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Understanding log probabilities of actions in the PPO objective
I'm trying to implement the Proximal Policy Optimization (PPO) algorithm (code here), but I am confused about certain concepts.
What is the correct way to implement log probability of a policy (...
3
votes
0
answers
41
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Batch PTA stopping condition
I am reviewing my Neural Network lectures and I have a doubt: My book's (Haykin) batch PTA describes a cost function which is defined over the set of the misclassified inputs.
I have always been ...
- 42.4k
3
votes
1
answer
521
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Extend the loss function from the single action to the n-action case per time step
My question concerns a side question (which was not answered) asked here:
How can policy gradients be applied in the case of multiple continuous actions?
I am trying to implement a simple policy ...
CommunityBot
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2
votes
1
answer
124
views
Custom Loss Function Traps Network in Local Optima
I am working with a feedforward neural network to fit the following simple function:
N(1) = -1
N(2) = -1
N(3) = 1
N(4) = -1
But I don't want to use the Mean-...
CommunityBot
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2
votes
0
answers
79
views
Can local learning rules minimize a global loss?
It is widely believed that synaptic plasticity is the way biological brains learn. Artificial implementations of this mechanism are for instance local weight-update rules in Spiking Neural Networks. ...
- 121
2
votes
0
answers
38
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How to create a loss function that penalizes duplicate indices in the output tensor?
We're working on a sequence-to-sequence problem using pytorch, and are using cross-entropy to calculate the loss when comparing the output sequence to the target sequence. This works fine and ...
- 121
2
votes
0
answers
60
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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 ...
- 4,062
2
votes
0
answers
64
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How to choose the new layer and objective function for transfer learning on a neural network?
I have a base model $M$ trained on a data say type 1 for task $T$. Now, I want to update $M$ by applying transfer learning for it to work on data type 2 for the same task $T$. I am very new to AI/ML ...
- 42.4k
2
votes
0
answers
46
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Is optimizing weighted sum multi objective tasks considered a multi-task learning?
I have two sequence prediction tasks, finding $\vec{\pi} \in \Pi$ and $\vec{\psi} \in \Psi$. Each sequence has its own objective function, i.e. $f_1(\vec{\pi})$ and $f_2(\vec{\psi})$. The input for ...
- 42.4k