Intuitionism, nonstandard arithmetic and functional interpretations
Por Bruno Dinis (Universidade de Lisboa, CMAF-CIO).
Por Bruno Dinis (Universidade de Lisboa, CMAF-CIO).
Por Alex Usvyatsov (Universidade de Lisboa, CMAF-CIO).
Por Gabriele Pulcini (FCT, Universidade Nova de Lisboa).
Pigeons do not jump high / Using o-minimality to compute lower bounds on sample complexity of neural networks (part 2)
Pigeons do not jump high 15h00
Por Ludovic Patey (Institut Camille Jordain, Lyon).
Por Alex Usvyatsov (Universidade de Lisboa, CMAF-CIO).
Abstract: I will discuss the concept of sample complexity in statistical learning theory. Then I will show how definability of many hypothesis classes (for example, essentially all artificial neural networks used in practice) in o-minimal structures, helps to compute tighter lower bounds on sample complexity for these hypothesis classes.
Por José Espírito Santo (Universidade do Minho).
Por Pedro Pinto (Universidade de Lisboa).
Por Alexander Usvyatsov (Universidade de Lisboa, CMAF-CIO).
Por Alexander Usvyatsov (Universidade de Lisboa, CMAF-CIO).
Abstract: These two talks are intended as a soft and not too technical introduction to model theory of metric structures, including a short history and motivating questions, with a particular emphasis on fundamentals of continuous first order logic. I will also mention a few successful applications to Banach space theory, as well as more recent promising directions.