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Questions tagged [regularization]

For questions about application of regularization techniques.

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9 views

Do L2 regularization and input normalization depend on sigmoid activation functions?

Following the online courses with Andrew Ng, he talks about L2 regularization (a.k.a. weight decay) and input normalization. Now, the argument is that L2 regularization make the weights smaller, ...
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19 views

Regularization of non-linear parameters?

I was wondering whether it is possible to regularize (L1 or L2) non-linear parameters in a general regression model. Say, I have the following non-linear least squares cost function, where $p$ is a $...
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47 views

Can dropout layers not influence LSTM training?

I am working on a project that requires time-series prediction (regression) and I use LSTM network with first 1D conv layer in Keras/TF-gpu as follows: ...
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1answer
76 views

What is the $\ell_{2, 1}$ norm?

I'm reading this paper and it says: In this paper, we present a multi-class embedded feature selection method called as sparse optimal scoring with adjustment (SOSA), which is capable of addressing ...
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114 views

Why is dropout favoured compared to reducing the number of units in hidden layers?

Why is dropout favored compared to reducing the number of units in hidden layers for the convolutional networks? If a large set of units leads to overfitting and dropping out "averages" the response ...
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17 views

L1 Reguarizer in Keras model throwing weight matrix dimension error

Was just experimenting with something when i ran into this error : I am getting matrix dimension errors only when i use L1 Regularizer. I have checked and the regularizer itself doesn't change the ...
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1answer
74 views

Dropout causes too much noise for network to train

I am using dropout of different values to train my network. The problem is, dropout is contributing almost nothing to training, either causing so much noise the error never changes, or seemingly ...
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32 views

What is the intuition behind the Label Smoothing?

I was learning about GAN when the term "Label Smoothing" appears. From the video tutorial that I watch, they use the term "label smoothing" to change the binary labels when calculating the loss of ...
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24 views

What is the benefit of scaling the hyperparameter C of an SVM?

Please read the following page of the Sklearn documentation. The figure shown there (see below) illustrates why C should be scaled when using a SVM with 'l1' penalty, whereas it shouldn't be scaled ...
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25 views

How can I model regularity?

I have data that are a result of rules that are exceptionless. I want to my program to 'look' at my data and figure out those rules. However, the data might contain what might look like an exception (...
2
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1answer
39 views

Should I remove the units of a neural network or increase dropout?

When adding dropout to a neural network, we are randomly removing a fraction of the connections (setting those weights to zero for that specific weight update iteration). If the dropout probability is ...
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65 views

Regarding L0 sparsification of DNNs proposed by Louizos, Kingma and Welling

I am reading the paper on $\ell_0$ regularization of DNNs by Louizos, Welling and Kingma (2017) (Link to arxiv). In Section 2.1 the authors define the cost function as follows: $$ \mathcal{R}\left( \...
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2k views

Why L1/L2 regularization technique did not improve my accuracy?

I am training a Multilayer Neural Nets with 146 samples (97 for training set, 20 for validation set and 29 for testing set). I am using: automatic differentiation, SGD method, fixed learning rate + ...
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152 views

How does L2 regularization make weights smaller?

I'm learning the Logistic Regression and L2 Regularization. The cost function looks like below. $$J(w) = -\displaystyle\sum_{i=1}^{n} (y^{(i)}\log(\phi(z^{(i)})+(1-y^{(i)})\log(1-\phi(z^{(i)})))$$ ...
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246 views

What is “early stopping” in machine learning?

What is early stopping in machine learning and, in general, artificial intelligence? What are the advantages of using this method? How does it help exactly? I'd be interested in perspectives and ...