What is a L0 regularization?
A type of regularization that penalizes the total number of nonzero weights in a model.
L0 regularization explained in plain English
A type of regularization that penalizes the total number of nonzero weights in a model. For example, a model having 11 nonzero weights would be penalized more than a similar model having 10 nonzero weights. L0 regularization is sometimes called L0-norm regularization.
L0 regularization is generally impractical in large models because L0 regularization turns training into a convex optimization problem. ---
Example
Practitioners refer to l0 regularization when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.
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