Tag
loss-functions
- Aug 27, 2026 Squared, Absolute, and Quantile Loss Compared by Their Gradients How the shape of a regression loss decides which observations move the fit, why the absolute loss has no derivative at zero, and what the pinball loss estimates instead of a mean. machine learning
- Jul 21, 2026 Gradient Boosting as Gradient Descent in Function Space Each boosting round fits a small tree to the negative gradient of the loss at the current predictions, which makes the algorithm a steepest-descent step whose direction comes from a restricted model class. machine learning
- Apr 25, 2022 Pointwise, Pairwise, and Listwise Training Objectives What each learning-to-rank formulation optimizes, why pairwise ranking losses match the evaluation better than regression, and what listwise gradients buy. information retrieval