Joan Garriga

Joan Garriga
Spanish National Research Council | CSIC · Centre de Estudis Avanc,ats de Blanes

Data Science Engineer
Data science engineer

About

17
Publications
3,504
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
159
Citations
Introduction
Centre de Estudis Avançats de Blanes, Spanish National Research Council (CEAB-CSIC). My research focuses in algorithms for Knowledge Discovery in Databases, with particular interest in Unsupervised Learning from high dimensional data.
Additional affiliations
June 2008 - June 2011
Universitat Politècnica de Catalunya
Position
  • Research Assistant

Publications

Publications (17)
Article
Full-text available
Dealing with sparsity is still an open question in data min-ing. As soon as the dimension of the sample space becomes high, the number of unseen events or rare configurations in the sample, contribute a great amount of uncertainty. Existing methodologies offer partial so-lutions, often based on assumptions about certainly unknown prior dis-tributio...
Conference Paper
Full-text available
We address the problem of assessing the information conveyed by a finite discrete probability distribution, within the context of knowledge discovery. Our approach is based on two main axiomatic intuitions: (i) the minimum information is given in the case of a uniform distribution, and (ii) knowledge is akin to a notion of richness, related to the...
Article
Full-text available
The Mosquito Alert dataset includes occurrence records of adult mosquitoes collected worldwide in 2014–2020 through Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes. Records are linked to citizen science-submitted photographs and validated by entomologists to determine the presence of five targeted...
Article
Full-text available
The Mosquito Alert dataset includes occurrence records of adult mosquitoes collected worldwide in 2014–2020 through Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes. Records are linked to citizen science-submitted photographs and validated by entomologists to determine the presence of five targeted...
Article
Full-text available
Global monitoring of disease vectors is undoubtedly becoming an urgent need as the human population rises and becomes increasingly mobile, international commercial exchanges increase, and climate change expands the habitats of many vector species. Traditional surveillance of mosquitoes, vectors of many diseases, relies on catches, which requires re...
Article
Full-text available
How animals explore and acquire knowledge from the environment is a key question in movement ecology. For pollinators that feed on multiple small replenishing nectar resources, the challenge is to learn efficient foraging routes while dynamically acquiring spatial information about new resource locations. Here, we use the behavioural mapping t-Stoc...
Article
Full-text available
Abstract Dispersal is one of the main determining factors of population structure. In the marine habitat, well-connected populations with large numbers of reproducing individuals are common but even so population structure can exist on a small-scale. Variation in dispersal patterns between populations or over time is often associated to geographic...
Preprint
Full-text available
Larval dispersal determines #population structure in marine organisms but is hard to measure precisely. Thanks to a great collaboration, we are trying to go one step further to the very fine scale of dispersal patterns.
Preprint
We introduce an improved unsupervised clustering protocol specially suited for large-scale structured data. The protocol follows three steps: a dimensionality reduction of the data, a density estimation over the low dimensional representation of the data, and a final segmentation of the density landscape. For the dimensionality reduction step we in...
Data
Generating the Results with the EMbC R-package. (PDF)
Article
What regard should a learning algorithm hold for the different information traces found in a sample? Answering this question objectively is not easy. Moreover, given that a full range of traits can be found in a human learning analogy, from the most daring or ingenuous, to the most conservative or in-credulous. Furthermore different interests are m...
Technical Report
Full-text available
In this document we give a brief overview on the use of the EMbC R-package with special emphasis on its use for behavioural annotation of animal's movement trajectories. For details about the EMbC algorithm please refer to (Garriga et. al 2015) and for further details about the package please refer to the package reference manual. 1 The EMbC Algori...
Article
Full-text available
We present a new algorithm for behavioural annotation. The EMbC algorithm (Expectation-Maximization binary Clustering) is a variant of the Gaussian Mixture Model maximum likelihood estimation algorithm, also known as Expectation-Maximization Clustering. We focus on the analysis of two movement variables (velocity and turn) obtained from the success...