This is a reference request. Strong convexity of the loss function is often used in theoretical analyses of convex optimisation for machine learning. My question is, are there important / widely used loss functions (or cost functions) being used in machine learning in practice? I know of the logistic loss for classification, and the square loss for regression. Are there any others?
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Another example is Hinge loss used in SVM.
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Also, L1 related loss: least absolute loss.
Combination between L1 and L2 regularization (https://en.wikipedia.org/wiki/Elastic_net_regularization).

Haitao Du
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