„Philosophical and optimisation aspects of Artificial Intelligence”
Prof. Yurii Nesterov
University of Budapest and CORE, UCLouvain
We discuss new challenges in the modern Science, created by Artificial Intelligence (AI). Indeed, AI requires a system of new sciences, mainly based on computational models. Their development has already started by the progress in Computational Mathematics. In this new reality, Optimization plays an important role, helping the other fields with finding tractable models and efficient methods, and significantly increasing their predictive power. We support our conclusions by several examples of efficient optimization schemes related to human activity.
Curriculum Vitae
Prof. Yurii Nesterov, awarded the World Laurate Association Prize is widely known as an inventor of the Fast Gradient Method (1983) and developer of Lexicographic Differentiation (1985). He is one of the creators of the modern theory of polynomial-time interior-point methods for structural convex optimization problems. In the book entitled “Interior-Point Polynomial Algorithms for Convex Programming”, co-authored with A. Nemirovskii, they introduced the theory of self-concordant functions to unify global complexity results obtained for convex optimization problems including linear, second-order cone and semidefinite programming. His subsequent achievements are related to development of Smoothing Technique (2005) and promotion of the higher-order methods (2019). The main impact of these results for practical computations consists in an extension of abilities of the optimization methods above the limits prescribed by complexity theory.
He got several international prizes and recognitions, among them there are
– Dantzig Prize from SIAM and Mathematical Programming society (2000)
– John von Neumann Theory Prize from INFORMS (2009)
– SIAM Outstanding paper award (2014)
– Euro Gold Medal from Association of European Operations Research Societies (2016)
– Member of Academia Europaea (2021) and National Academy of Sciences (USA, 2022)
– Lanchester prize from INFROMS (2022)
„Statistical & numerical algebra based analysis and soft modelling in human-subject experiments”
Prof. Péter Baranyi
Corvinus University of Budapest, Hungary
coming soon
Curriculum Vitae
Peter Baranyi, a renowned Hungarian scholar, has made significant contributions to the fields of non-linear control theory & modelling, as well as the cognitive aspects of digital reality. In 2010, he introduced the concept of Cognitive Info-Communications, which focuses on the new cognitive capabilities of the blended combination of human and informatics. One of his notable inventions is the TP model transformation, a higher-order singular value decomposition of continuous functions. This transformation plays a crucial role in the development of nonlinear control design theories and paves the way for optimization techniques. Baranyi’s scientific achievements have been recognized with prestigious awards, including the Investigator Award from Sigma Xi and the International Design Gabor Award. He has published over 100 journal papers and authored three books. In 2006, he was honoured with a doctorate from the Hungarian Academy of Sciences.