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Project

Declarative modeling for machine learning and data mining.

Declarative models specify what conditions need to satisfied in order to obtain a solution to a specific problem. Declarative models contrast with the traditional procedural approach which specify how such solutions must be computed. A declarative modeling paradigm will be developed and applied to the areas of machine learning, data mining and experimentation. The declarative modeling paradigm that we will pursue consists of three key components: A modeling language (M language) which is a high level declarative language for specifying the relevant domain knowledge, independent of a particular task (M component). A solver which accepts input in a more low-level task-oriented language (S language) and performs a particular computational task (S component). A programming platform in which a user employs a general purpose language to solve a specific computational task. Today, there exist no general declarative approaches to machine learning, data mining and experimentation. Therefore, contrasting these domains with contemporary approaches to declarative modeling (pursued in knowledge representation and constraint programming) forms an ideal setup for realizing breakthroughs in declarative modeling as well as in machine learning, data mining and experimentation.
Date:1 Jan 2013 →  31 Dec 2017
Keywords:Experimentation, Data Mining, Artificial Intelligence, Machine Learnin, Knowledge Representation, Declarative Modeling, Constraint programming
Disciplines:Applied mathematics in specific fields