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2023-T3 Recent Trends in Computer Algebra

Fundamental Algorithms and Algorithmic Complexity

Institut Henri Poincaré
Amphithéâtre Hermite / Darboux
11 rue Pierre et Marie Curie
75005 Paris

Fundamental Algorithms and Algorithmic Complexity

September 25-29, 2023 - IHP, Paris

Workshop with special week

Special week. September 18 to 22, 2023

  • Efficient Algorithms for Integer and Polynomial Matrices (long course, Monday to Friday), G. Labahn and A. Storjohann
  • Euclidean Lattices (short course, Monday and Tuesday), D. Stehlé
  • General audience presentation, Wednesday 20th, J. van der Hoeven

Workshop: Fundamental Algorithms and Algorithmic Complexity

September 25 to 29, 2023

Organizers: J. van der Hoeven, M. Giesbrecht, P. Koiran, G. Villard

The field of computational complexity aims at understanding the capabilities of computational devices and especially how fast various problems can be solved. A lot of research focuses on isolating and studying complexity classes of those problems that can be solved using a certain amount of resources. One of the most interesting and challenging problem in the area of computer algebra, is to develop tools and methods in complexity theory that also reflects running times that are observed in practice, for a wide selection of data types. The computer algebra research community indeed produces software that proceed on various mathematical objects and having high impact. This requires expertise from many areas of computer science and of mathematics.

This workshop aims at bringing together experts from both the theoretical and more practical sides, while covering a wide spectrum of problems from algebra, geometry, symbolic computation, arithmetic, and numerical computation. Specific challenges that the workshop will focus on include the following: polynomials in complexity, structured problems, tensors, complexity and specification, certificates and their links with delegated computation, efficiency in crypto-algebro algorithms, HPC implementation of core algorithms, complexity in numerical analysis.