Introduction to Tropical Geometry and its Applications to Machine Learning

Tropical geometry is a relatively recent field in mathematics and computer science combining elements of algebraic geometry and polyhedral geometry. It has recently emerged in the study of deep neural networks (DNNs) and other machine learning systems. In this talk Prof. Petros Maragos will first summarize introductory ideas and tools of tropical geometry and its underlying max-plus algebra. Then, he will focus on how this new set of tools can aid in the analysis, design and understanding of several classes of neural networks and other machine learning systems, including DNNs with piecewise-linear (PWL) activations, morphological neural networks, and nonlinear regression with PWL functions. His coverage will include studying the representation power, training and pruning of these networks and regressors under the lens of tropical geometry and algebra. More information and related papers can be found here.

Tuesday, 10-26-2021, 05.00 p.m. – 06.00 p.m., virtual event

Further details at:

This is a event of I-AIDA – International Artificial Intelligence Doctoral Academy.