1st Lisbon Machine Learning School
Date: July 20-25, 2011*
Place: Instituto Superior Técnico (IST), Universidade Tecnica de Lisboa, Portugal
Organizers: jointly by IST, the Instituto de Telecomunicações and the Spoken Language Systems Lab - L2F of INESC-ID
Call for Participation: To apply, please send a brief summary of your research interests (maximum 1 page) along with your CV mentioning name, country, and affiliation to: firstname.lastname@example.org.
In its debut year, the topic of the school is "Learning for the Web." 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.
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 assumed;
- Recommended reading will be provided in advance;
- Includes a strong practical component;
- A day zero is scheduled to review basic concepts and introduce the necessary tools for implementation exercises;
- Days will be divided into tutorials and practical sessions (view schedule);
- Both basic and advanced topics will be covered;
- Instructors are leading researchers in machine learning.
List of Speakers:
- MÁRIO FIGUEIREDO - Instituto Superior Técnico | Portugal
- KOBY CRAMMER - Technion, Israel Institute of Technogly | Israel
- BEN TASKAR - University of Pennsylvania | USA
- NOAH SMITH - Carnegie Mellon University | USA
- JASON EISNER - Johns Hopkins University | USA
- XAVIER CARRERAS - Universitat Politècnica de Catalunya | Spain
- FERNANDO PEREIRA - Google Inc. | USA
- Application Deadline: March 31, 2011
- Decision: April 15, 2011
- Early Registration: May 31, 2011
- Summer School: July 20-26, 2011 (right in-between UAI and EMNLP)
*Note the convenient timeframe, strategically collocated in-between important ML and NLP conferences that are held nearby: IJCAI, UAI, and EMNLP.