The 2022 Lisbon Machine Learning Summer School (LxMLS 2022) will take place between July 24th and July 29th at the Congress Center of Instituto Superior Técnico. For the second year, CMU Portugal proudly associates with this yearly reference event.
The school covers a range of machine learning topics, from theory to practice, that are important in solving natural language processing (NLP) problems arising in different application areas. It is organized jointly by Instituto Superior Técnico (Técnico), Instituto de Telecomunicações, 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, with the support of the CMU Portugal Program.
This year’s edition returns as an in-person 6-day event after two years online due to Covid restrictions. The deadline for applications is May 15th, 2022, and the application form is available online.
Other useful information:
* Application Deadline: May 15, 2022
* Decision: June 1, 2022
* Summer School: July 24 – 29, 2022
Topics and Intended Audience
The school will cover a range of Machine Learning (ML) topics, from theory to practice, that are important in solving Natural Language Processing (NLP) problems that arise in the analysis and use of Web data.
The target audience is:
* Researchers and graduate students in the fields of NLP and Computational Linguistics;
* Computer scientists who have interests in statistics and machine learning;
* Industry practitioners who desire a more in depth understanding of these subjects.
Features of LxMLS
* No deep previous knowledge of ML or NLP is required, but the attendants are assumed to have some basic background on mathematics and programming;
* Days are divided into morning lectures and afternoon lab sessions and practical talks;
* The guide for the labs will be provided one month in advance. You can check here the guide used in previous editions.
* A day zero is scheduled to review basic concepts and introduce the necessary tools for implementation exercises
* Lecturers are leading researchers in machine learning and natural language processing
Any other questions should be directed to: firstname.lastname@example.org.