Creating and sharing knowledge for telecommunications

Lisbon Machine Learning Summer School (LxMLS)


on 24-07-2022

... The Lisbon Machine Learning Summer School (LxMLS) takes place yearly at Instituto Superior Técnico (IST). LxMLS 2022 will be a 6-day event (24-29 July 2022), scheduled to take place as an in-person event.

The school covers a range of machine learning topics, from theory to practice, important for solving natural language processing problems arising in different application areas.

It is organized jointly by Instituto Superior Técnico (IST), a leading Engineering and Science school in Portugal, the Instituto de Telecomunicações, the Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa (INESC-ID), the Lisbon ELLIS Unit for Learning and Intelligent Systems (LUMLIS), and Unbabel.

This Summer School addresses mainly researchers and graduate students in the fields of NLP and Computational Linguistics, computer scientists interested in statistics and machine learning, and industry practitioners who desire a more in-depth understanding of these subjects.

No deep previous knowledge of ML or NLP is required, but the attendants are assumed to have some basic background in mathematics and programming. A day zero is scheduled to review basic concepts and introduce the necessary tools for implementation exercises.

Important dates
Application Deadline: May 15th
Notification of Admission: June 1st
Summer School: July 24th-29th


To know everything about this event, please visit LxMLS webpage:
http://lxmls.it.pt/2022/


Apply here: More Information..

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


on 05-07-2022

... 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 Amphitheaterre 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 | “Accelerating the understanding of nonlinear dynamical systems using machine learning” by Frederico Fiuza


The workshop will be also transmitted by Zoom. Here's the link: https://videoconf-colibri.zoom.us/j/91599759679


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


To know more about this project, follow the link: More Information..