Prof. ScD. Boris Goldengorin is Full Professor at the Department of Discrete Mathematics, MIPT. He is the inventor and author of data-correcting and tolerance-based algorithms with applications in Operations Management, Quantitative Logistics, Industrial Engineering, and Computer Vision. He is the author of Cell Formation in Industrial Engineering (Springer) and pioneer of the pseudo-Boolean polynomial approach to data analysis.

Fundamentals of Data Analysis, AI and Computer Vision                                                                                                                                                                                                                                                     Abstract : We start our presentation with the transformation of an arbitrary matrix with numerical data into a pseudo-Boolean polynomial (pBp) aggregating its similar monomials induced by different columns into a single monomial extracting and combining any tiny distinctions of different columns [1]. At the next step we apply the Dilworth theorem [2] returning the proved minimum number of aggregated columns compared to the given matrix. Further data simplification is based on the Truncation Theorem removing not essential tails per each aggregated column which is useful to enhance the computational efficiency in solving different optimization problems in Data Analysis [3], Artificial Intelligence [4, 5] and Computer Vision [6].                                                                                                                                                                                                                     Keywords: Pseudo-Boolean polynomial, Dilworth theorem, Data aggregation, Computer vision