Structured learning is the subfield of machine learning

Machine learning

Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases...

 concerned with computer programs that learn to map inputs to arbitrarily complex outputs. This stands in contrast to the simpler approaches of classification, where input data (instances) are mapped to "atomic" labels, i.e. symbols without any internal structure, and regression

Regression analysis

In statistics, regression analysis includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables...

, where inputs are mapped to scalar numbers.

Algorithms and models for structured learning include inductive logic programming

Inductive logic programming

Inductive logic programming is a subfield of machine learning which uses logic programming as a uniform representation for examples, background knowledge and hypotheses...

, structured SVM

Structured SVM

The structured support vector machine is a machine learning algorithm that generalizes the Support Vector Machine classifier. Whereas the SVM classifier supports binary classification, multiclass classification and regression, the structured SVM allows training of a classifier for general...

s, conditional random field

Conditional random field

A conditional random field is a statistical modelling method often applied in pattern recognition.More specifically it is a type of discriminative undirected probabilistic graphical model. It is used to encode known relationships between observations and construct consistent interpretations...

s, Markov logic network

Markov logic network

A Markov logic network is a probabilistic logic which applies the ideas of a Markov network to first-order logic, enabling uncertain inference...

s and Constrained Conditional Models

Constrained Conditional Models

A Constrained Conditional Model is a machine learning and inference framework that augments the learning of conditional models with declarative constraints. The constraint can be used as a way to incorporate expressive prior knowledge into the model and bias the assignments made by the learned...

.