Hierarchical linear subspace indexing method
R – INESC-ID Lisboa –
Traditional multimedia indexing methods are based on the principle of hierarchical clustering of the data space, in which metric properties are used to build a tree that then can be used to prune branches while processing the queries. However, the performance of these methods will deteriorate rapidly when the dimensionality of the data space is increased.
Based on the generic multimedia indexing (GEMINI) approach and lower bounding methods a hierarchical linear subspace indexing method will be described, which does not suffer from the dimensionality problem. The hierarchical subspace approach offers a fast searching method for large content-based multimedia databases.
The approach will be demonstrated on image indexing, in which the subspaces correspond to different resolutions of the images. During content-based image retrieval the search starts in the subspace with the lowest resolution of the images. In this subspace the set off all possible similar images is determined. In the next subspace additional information corresponding to a higher resolution is used to reduce this set. This procedure is repeated until the similar images can be determined eliminating the false candidates.
The developed methods of analysis can be generalized for all means of content-based access methods that are based on information loss techniques, like for example hierarchical clustering which relies on stepwise digitalization of the space rather then the reduction of its dimension.
Date: 2006-Mar-10 Time: 14:00:00 Room: 336
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Research data repositories and tools for human genomics data sharing
Inform the human research community of the status and availability of BioData.pt Local EGA and discuss its need and usability challenges.
The European Genome-phenome Archive (EGA) is a repository for all sequence and genotype experiment types, including case-control, population, and family studies. The EGA will serve as a permanent archive that will archive several levels of data, including the raw data (which could, for example, be re-analysed in the future by other algorithms) as well as the genotype calls provided by the submitters.
Responding to national regulations over human data sharing and other constraints, BioData.pt deploys and operates a Local EGA instance and tools that allow data discovery of genomic and phenoclinic data, following the GA4GH standard and international best practices.
This workshop aims at informing the human research community of the status and availability of BioData.pt Local EGA and discuss from several perspectives its need and usability challenges.
Further details and registration are available here.
OLISSIPO Summer School in Lisbon | Computational phylogenetics to analyse the evolution of cells and communities
We are happy to announce the OLISSIPO Summer School on Computational phylogenetics to analyse the evolution of cells and communities, which will be held in Lisbon, Portugal, at INESC-ID, between July 2-7, 2023.
David Posada, University of Vigo (class)
João Alves, University of Vigo (hands-on)
Nadia El-Mabrouk, Université de Montréal (class)
Mattéo Delabre, Université de Montréal (hands-on)
Ran Libeskind-Hadas, Claremont McKenna College (class and hands-on)
Russell Schwartz, Carnegie Mellon University (class and hands-on)
See the preliminary agenda at: https://olissipo.inesc-id.pt/tree-tango-school
Registration is mandatory. You can register at: https://forms.gle/VsASFHW5E7MJvaCc9
The registration fee is 250€ for students and OLISSIPO members and 350€ for postdocs or other researchers (meals indicated at the schedule of the school are included, accommodation and flights are not). All details will be made available upon registration.
We will have slots for flash talks (3-10 min depending on the number of submissions) to present yourself and the work you have been developing in your research.
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The Lisbon Machine Learning Summer School (LxMLS) takes place yearly at Instituto Superior Técnico (IST). LxMLS 2023 will be a 6-day event (14-20 July, 2023), scheduled to take place as an in-person event.
The school covers a range of machine learning topics, from theory to practice, that are important in 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), Unbabel, Zendesk, and IBM Research.
Check online 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, LxMLS 2021, LxMLS 2022 (you can also watch the videos of the lectures for 2016, 2017, 2018, and 2020).
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ISD 2023 will be hosted by Instituto Superior Técnico, in Lisbon, Portugal, on August 30–September 1, 2023.