13th Lisbon Machine Learning School, with CMU Portugal support

The 2023 edition of the Lisbon Machine Learning Summer School (LxMLS 2023) will take place between July 14th and July 20th at the Congress Center of Instituto Superior Técnico. For the third year, the CMU Portugal Program proudly associates with this yearly reference event with over one decade of existence. 

The LxMLS 2023 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 (IT) , Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento (INESC-ID), the Lisbon ELLIS Unit for Learning and Intelligent Systems (LUMLIS), and Unbabel, Zendesk, and IBM Research, with the support of the CMU Portugal Program.

The deadline for applications is April 28th, 2023, and the application form is available online.

Among the invited speakers and Instructors are CMU Portugal Faculty members from IT/Técnico (Universidade de Lisboa) André Martins and Mário Figueiredo, who are also the main organizers. André is also a CMU Portugal Alum currently working as VP of AI Research at Unbabel, a CMU Portugal Industrial Affiliate company.

From Carnegie Mellon University, the event will count on CMU Portugal faculty member Bhiksha Raj, from the Language Technologies Institute. 

As an organizer of this year’s edition is Zita Marinho, Research Scientist at DeepMind and a Dual Degree Ph.D. alumna in Computer Science – Robotics at Técnico and CMU Robotics Institute.

As part of the steering Committee are Isabel Trancoso, CMU Portugal Faculty & Researcher, and Fernando Pereira from Google and a CMU Portugal External Review Committee member. 

More about the School Schedule and Instructors is available on the LxMLS 2023 website.

Other useful information:

Important Dates
* Application Deadline: April 28, 2023
* Notification of Admission: May 12, 2023
* Early registration: May 12 – June 30, 2023
* Summer School: July 14 – 20, 2023

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
* Computer scientists who have interests in statistics and machine learning;
* Industry practitioners who desire a more in-depth understanding of these

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 (see schedule);
* The Labs guide will be provided one month in advance. Last year’s guide is
available on the website.
* The first day is scheduled to review basic concepts and introduce the
necessary tools for implementation exercises
* Both basic (e.g linear classifiers) and advanced topics (e.g. deep
learning and transformers) will be covered
* Welcome reception, Banquet, daily lunch as well as morning and afternoon
coffee breaks are included in the application fee
* Lecturers are leading researchers in machine learning and natural language

List of Confirmed Speakers

  • ADÈLE H. RIBEIRO Columbia University | USA 
  • ANDRÉ MARTINS University of Lisbon & Unbabel | Portugal 
  • BHIKSHA RAJ Carnegie Mellon University | USA
  • DESMOND ELLIOTT University Of Copenhagen | Denmark 
  • KYUNGHYUN CHO New York University | USA 
  • MÁRIO FIGUEIREDO University of Lisbon & Instituto de Telecomunicações | Portugal 
  • NOAH SMITH University of Washington & Allen Institute for Artificial Intelligence | USA 
  • SARA HOOKER Cohere for AI |Canada 
  • SLAV PETROV Google Inc. | USA 
  • WILKER AZIZ University Of Amsterdam | Netherlands 
  • YEJIN CHOI University of Washington | USA

Any other questions should be directed to: lxmls-2023@lx.it.pt.

Start date

Jul. 14, 2023

End Date

Jul. 20, 2023