For questions related to $L_2$ regularization (aka ridge regression or weight decay), a special case of Tikhonov regularization where the Tikhonov matrix is a multiple of the identity matrix.
Questions tagged [l2-regularization]
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How does L2 regularization make weights smaller?
I'm learning logistic regression and $L_2$ regularization.
The cost function looks like below.
$$J(w) = -\displaystyle\sum_{i=1}^{n} (y^{(i)}\log(\phi(z^{(i)})+(1-y^{(i)})\log(1-\phi(z^{(i)})))$$
And the regularization term is added. ($\lambda$ is a…
Riddle Aaron
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When is using weight regularization bad?
Regularization of weights (e.g. L1 or L2) keeps them small and standardized, which can help reduce data overfitting. From this article, regularization sounds favorable in many cases, but is it always encouraged? Are there scenarios in which it…
mark mark
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Why does L1 regularization yield sparse features?
In contrast to L2 regularization, L1 regularization usually yields sparse feature vectors and most feature weights are zero.
What's the reason for the above statement - could someone explain it mathematically, and/or provide some intuition (maybe…
stoic-santiago
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Which is a better form of regularization: lasso (L1) or ridge (L2)?
Given a ridge and a lasso regularizer, which one should be chosen for better performance?
An intuitive graphical explanation (intersection of the elliptical contours of the loss function with the region of constraints) would be helpful.
jaeger6
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Would either $L_1$ or $L_2$ regularisation lower the MSE on the training and test data?
Consider linear regression. The mean squared error (MSE) is 120.5 for the training dataset. We've reached the minimum for the training data.
Is it possible that by applying Lasso (L1 regularization) we would get a lower MSE for the training data?…
user6394019
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Does L1/L2 Regularization help reach an optimum result faster?
I understand that L1 and L2 regularization helps to prevent overfitting. My question is then, does that mean they also help a neural network learn faster as a result?
The way I'm thinking is that since the regularization techniques reduce weights…
Mark
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How do L2 norm and Jacobian act as a regularisation term to encourage smoothness in a deformation field?
How do L2 norm and The Jacobian act as a regularisation term to encourage smoothness in a deformation field? from the VoxelMorph original paper (here) they used Jacobian as a means to smoothen the deformation field, a similar paper (here) made use…
a__ys
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Why does L1/L2 regularization not prevent co-adaptation?
I thought L2 regularization decrease a length of weight vector by almost removing many weights.
So, it would result that output neurons' activations are sparse and then less effected of co-adaptation like using dropout.
I saw somewhere L1/L2…
김동완
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What is the effect of too harsh regularization?
While training a CNN model, I used an l1_l2 regularization (i.e. I applied both $L_1$ and $L_2$ regularization) on the final layers. While training, I saw the training and validation losses are dropping very nicely, but the accuracies aren't…
Sepehr Golestanian
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