Tereso del Rio Almajano

Tereso del Rio Almajano

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Personal profile

Research Interests

I'm interested in the use of heuristics and machine learning to speed up these algebraic processes without affecting the mathematical validity of the results.

Many algebraic algorithms that are proving themselves very useful in areas using applied mathematics, for example, Cylindrical Algebraic Decomposition (CAD), non-uniformal Cylindrical Algebraic Decomposition (nuCAD) or Cylindrical Algebraic Covering (CAC). However, they have a huge complexity (double exponential w.r.t. the number of variables) and therefore some interesting problems can't be solved in a reasonable time.

In these algebraic algorithms some choices must be taken, such as a variable ordering or whether it's worth it to use some extra information that might take some time to compute. These choices can be taken using Machine Learning and they have the ability to affect immensely the resources used to find the answer but they don't affect the mathematical validity of the results. Finding, therefore, a way of helping back the field of Mathematics using Machine Learning.

Education/Academic qualification

Investigation on Mathematics, MSc, University of Valladolid

31 Oct 201923 Jul 2020

Award Date: 23 Jul 2020

Mathematics, Degree, University of Valladolid

5 Sep 201531 Oct 2019

Award Date: 31 Oct 2019

Erasmus on Mathematics, University of Dundee

5 Sep 201820 Jun 2019

Keywords

  • QA76 Computer software
  • Computational and Applied Algebraic Geometry
  • Machine Learning
  • Symbolic Computation

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