Recent work has shown that including the optimization problem as alayer in the model training pipeline results in predictions oftheunobservedparameters thatlead tohigher decision quality.

In online multiclass classification a learner has to repeatedly predict the label that corresponds to a feature vector. Algorithms in this setting have a wide range of applications ranging from predicting the outcomes ofsport matches torecommender systems.

However, this assumption does not always hold in practice.