All Questions
7 questions
1
vote
0
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29
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Is this a reasonable way to transform simple MSE loss function to weighted MSE for neural networks?
The idea is tested on a dataset with a clear outlier (see picture below)
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- 516
0
votes
0
answers
33
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What is the network structure of Ademxapp Model A1 Trained on Cityscapes Data in the Mathematica?
I want to implement the model (Ademxapp Model A1 Trained on Cityscapes Data) on my data for segmentation, so I need the partial structure of this model, can anyone help?
- 195
8
votes
1
answer
187
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Optimize a network topology?
I'd like to know if one can use optimization function like Maximize[] or BayesianMaximize[] to optimize the hyper-parameters of ...
- 27.8k
5
votes
0
answers
158
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How to train each layer in a Neural Network so they optimize different loss functions in an adversarial network?
Example NetGraph to illustrate the idea (Input is an online signal with a value between -1 and 1, Noise is Gaussian Centered at 0 and standard deviation 0.1, EvilNet is constrained to output a value ...
- 526
2
votes
0
answers
107
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Specifying feature types for BayesianMinimization
I'd like to use Bayesian optimization over a pair of features, one nominal, one numerical. If I do something like this:
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- 42.3k
5
votes
0
answers
157
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What's BayesianMinimization and related functions based on?
Is it specified anywhere what the backend is for the Bayesian optimization related functionality in Mathematica v11? I'm specifically referring to the Bayesian* ...
- 1,002
2
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0
answers
1k
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Stochastic Gradient Descent with constraints
Let's say we have a convex objective function $f(\textbf{x})$, with $\textbf{x}\in R^n$ which we want to minimise under a set of constraints. The problem is that calculating $f$ exactly is not ...
- 841