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Workshop on Interactions Between Nonextensive Entropies, Machine Learning, Language, and Physics


on 05-07-2022

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Project DeepSPIN is organising the Workshop on Interactions Between Nonextensive Entropies, Machine Learning, Language, and Physics on July 5, 2022, which will be held on IST's Amphitheater Abreu Faro, in the Interdisciplinary Complex.

Nonextensive statistical mechanics [1] is a generalization of the standard Boltzmann-Gibbs theories of statistical mechanics, inspired by the seminal work of Constantino Tsallis. This generalized theory has had a very strong impact in many disciplines and a wide range of applications, including statistical mechanics, thermodynamics, information geometry, statistics, machine learning, and natural language processing.

In this interdisciplinary workshop, will be present Constantino Tsallis, as well as speakers from several disciplines, ranging from mathematics and physics to machine learning and language, who will discuss their use of nonextensive entropies and Tsallis statistics on various applications, namely, Mário Figueiredo, Ben Peters, André Martins, José Mourão, and Frederico Fiuza.


Program:

11:00 - 12:00 | "Why is it easier to understand what is energy than what is entropy?" by Constantino Tsallis

14:00 - 14:30 | "Tsallis entropies and kernel methods" by Mário Figueiredo

14:30 - 15:00 | "Tsallis entropies and entmax for language generation" by Ben Peters

15:00 - 15:45 | "From Sparse Modeling to Sparse Communication" by André Martins

(Coffee break)

16:00 - 16:3 | “Training deep neural networks: replace gradient descent by the Feynman path integral and possible extension to the nonextensive formalism” by José Mourão

16:30 - 17:00 | Frederico Fiuza, TBD



[1] Tsallis, Constantino, "Introduction to nonextensive statistical mechanics: approaching a complex world." Springer 1.1 (2009): 2-1


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