11th Lisbon Machine Learning Summer School

11th Lisbon Machine Learning Summer School

LxMLS 2021 will take place July 7th to July 15th in online format (via zoom and slack). 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), Unbabel and Cleverly.

Click here for information about past editions (LxMLS 2011, LxMLS 2012, LxMLS 2013, LxMLS 2014, LxMLS 2015, LxMLS 2016, LxMLS 2017, LxMLS 2018, LxMLS 2019, LxMLS 2020) and to watch the videos of the lectures (2016, 2017, 2018, 2020).

 

Call for Participation

Important Dates
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* Application Deadline: May 15, 2021
* Decision: June 1, 2021
* Early Registration: June 15 – July 1, 2021
* Summer School: July 7 – 15, 2021


Topics and Intended Audience
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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.

Our 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
  • Lecturers are leading researchers in machine learning and natural language processing (see speakers)
  • 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 can be found here
  • A day zero 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, reinforcement learning) will be covered



Online Format:

Due to the current COVID-19 pandemic, the 11th Lisbon Machine Learning School will be held online (via zoom and slack). Similar to last year, we are excited for the opportunity to create a virtual school, where you will be able to attend all the lectures, and participate in the Q&As and labs remotely. We will also provide the tools for students to engage with each other remotely. The lectures will also be streamed to YouTube, and will become freely available later in our YouTube channel. The Q&A, labs and social activities will remain restricted to the accepted students only.

List of Confirmed Speakers
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LUIS PEDRO COELHO Fudan University | China
MÁRIO FIGUEIREDO Instituto de Telecomunicações & Instituto Superior Técnico | Portugal
ANDRE MARTINS Instituto de Telecomunicações & Unbabel | Portugal
IRYNA GULEYVICH Technical University Darmstat | Germany
NOAH SMITH University of Washington & Allen Institute for Artificial Intelligence | USA
SLAV PETROV Google Inc. | USA
XAVIER CARRERAS dMetrics | USA
GRAHAM NEUBIG Carnegie Mellon University | USA
BHIKSHA RAJ Carnegie Mellon University | USA
CHRIS DYER Google Deep Mind | UK
ELIAS BARENBOIM Columbia University | USA
ADELE RIBEIRO Columbia University | USA
STEFAN RIEZLER Institut für Computerlinguistik, Universität Heidelberg | Germany
BARBARA PLANK IT University of Copenhagen | Denmark
SASHA RUSH Cornell Tech | USA

Please visit the webpage for up to date information: http://lxmls.it.pt/2021

To apply, please fill the form in https://lisbonmls.wufoo.com/forms/application-form-lxmls-2021/
Any questions should be directed to: lxmls-2021@lx.it.pt.

The event is finished.

About INESC-ID

INESC-ID, “Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento em Lisboa” is a Research and Development and Innovation Organization (R&D+i) in the fields of Computer Science and Electrical and Computer Engineering. INESC-ID mission is to produce added value to people and society, supporting the response of public policies to scientific, health, environmental, cultural, social, economic and political challenges. INESC-ID promotes cooperation between academia and industry by addressing research on daily life issues, such as healthcare, space, mobility, agri-food, industry 4.0, and smart grids. This high level of knowledge transfer is achieved through both competitive research projects and direct contracted research. Public and private entities have therefore access to a pool of knowledge, resources and services provided through the unique competencies available at the institution.

 

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