Minimum Description Length Codes Are Critical

Minimum Description Length Criterion

he intelligibility of speech in communication systems is generally reduced by interfering noise. This interference, which can take the form of environmental noise, reverberation, competing speech, or electronic channel noise, reduces intelligibility by masking the signal of interest. The reduction in intelligibility is particularly troublesome for listeners with hearing impairments, who have gr...

Minimum Description Length Principle

The minimum description length (MDL) principle states that one should prefer the model that yields the shortest description of the data when the complexity of the model itself is also accounted for. MDL provides a versatile approach to statistical modeling. It is applicable to model selection and regularization. Modern versions of MDL lead to robust methods that are well suited for choosing an ...

The Minimum Description Length

Minimum Description Length Principle: Generators Are Preferable to Closed Patterns

The generators and the unique closed pattern of an equivalence class of itemsets share a common set of transactions. The generators are the minimal ones among the equivalent itemsets, while the closed pattern is the maximum one. As a generator is usually smaller than the closed pattern in cardinality, by the Minimum Description Length Principle, the generator is preferable to the closed pattern...

Pruning with Minimum Description Length

The number of parameters in a model and its ability to generalize on the underlying data-generating machinery are tightly coupled entities. Neural networks consist usually of a large number of parameters, and pruning (the process of setting single parameters to zero) has been used to reduce the nets complexity in order to increase its generalization ability. Another less obvious approach is to ...