13-11-2024
The Center of Mathematics and Applications (NOVA Math), promote the Seminar of Algebra and Logic with the title: “Algebraic Machine Learning”. Fernando Martin-Maroto (Champalimaud Foundation, Algebraic AI) is the speaker.
Abstract: I will give a brief introduction to Algebraic Machine Learning (AML), a purely algebraic method that does not use statistics, search or optimization. Instead, AML relies on semantic embeddings in semilattices and subdirect decompositions. AML is capable of learning from data and also from just a problem statement in the form of a set of formulas; for example, AML can learn to find Hamiltonian Cycles from the problem statement. With the same algorithm, AML can learn from data (e.g. classifying medical images) with a test accuracy that rivals that of deep multilayer perceptrons. I will also give an introduction to Atomized Semilatices, a mathematical method developed to operate and compute AML models.
Wednesday, 18 december, from 14:00 to 15:00.