Questions tagged [l1-regularization]
For questions related to $L_1$ regularization, also known as LASSO regularization.
8
questions
1
vote
0
answers
47
views
Since ReLU activations also result in a sparse network, does it have the same "feature selection" property as L1 regularization?
From Deep Learning (Courville, Goodfellow, Bengio), a ReLU activation often "dies" because
One drawback to rectified linear units is that they cannot learn via gradient based methods on ...
- 11
1
vote
0
answers
42
views
How to prove that a regularisation method simplified a neural network?
There are a few ways to regularise a neural network, for example dropout or the L1. Now, both these methods, and possibly most other regularisation methods, tend to remove from, or simplify the neural ...
- 206
2
votes
1
answer
584
views
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) ...
- 123
0
votes
0
answers
39
views
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 ...
4
votes
0
answers
62
views
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 ...
- 753
4
votes
1
answer
139
views
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 ...
- 1,121
2
votes
1
answer
108
views
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 ...
- 233
3
votes
1
answer
123
views
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 ...
- 308