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Recent Submissions
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Effective visualization of sparse image-to-image correspondences
(European Association for Computer Graphics (Eurographics), 2020)
Conference report
Open AccessFinding robust correspondences between images is a crucial step in photogrammetry applications. The traditional approach to visualize sparse matches between two images is to place them side-by-side and draw link segments ... -
A Tool for N-way analysis of programming exercises
(European Association for Computer Graphics (Eurographics), 2020)
Conference report
Open AccessProgramming exercises are a corner stone in Computer Science courses. If used properly, these exercises provide valuable feedback both to students and instructors. Unfortunately, the assessment of student submissions through ... -
An interoperable workflow-based framework for the automation of building intelligent process control systems
(International Environmental Modelling and Software Society (iEMSs), 2018)
Conference lecture
Open AccessOne of the major problems to design and implement a control/supervision system for a process lies in the need to establish an ad-hoc system for each process installation. On the other side, an open challenge related to the ... -
Convolutional Neural Networks, image recognition and financial time series forecasting
(2019)
Conference report
Restricted access - publisher's policyConvolutional Neural Networks (CNN) are best known as good image classifiers. This model is recently been used for financial forecasting. The purpose of this work is to show that by converting financial information into ... -
Do Google Trends forecast bitcoins? Stylized facts and statistical evidence
(2019)
Conference report
Open AccessIn early 2018 Bitcoin prices peaked at USD 20,000 and, almost two years later, we still continue debating if cryptocurrencies can actually become a currency for the everyday life or not. From the economic point of view, ... -
Random forest as a tumour genetic marker extractor
(IOS Press, 2019)
Conference report
Open AccessFinding tumour genetic markers is essential to biomedicine due to their relevance for cancer detection and therapy development. In this paper, we explore a recently released dataset of chromosome rearrangements in 2,586 ... -
From bilingual to multilingual neural machine translation by incremental training
(Association for Computational Linguistics, 2019)
Conference lecture
Open AccessMultilingual Neural Machine Translation approaches are based on the use of task specific models and the addition of one more language can only be done by retraining the whole system. In this work, we propose a new training ... -
On some strategies for missing values in positive semidefinite matrices
(Thompson, 2005)
Conference report
Open AccessThis article presents our work on missing values in Positive Semi-Definite or PSD matrices. We show how simple properties of PSD matrices can be used to deal with missing values. We study several situations and investigate ... -
Multilingual, multi-scale and multi-layer visualization of sequence-based intermediate representations
(Association for Computational Linguistics, 2019)
Conference report
Restricted access - publisher's policyThe main alternatives nowadays to dealwith sequences are Recurrent Neural Net-works (RNN), Convolutional Neural Networks(CNN) architectures and the Transformer. Inthis context, RNN’s, CNN’s and Transformerhave most commonly ... -
Similarity-based heterogeneous neuron models
(IOS Press, 2000)
Conference report
Open AccessThis paper introduces a general class of neuron models, accepting heterogeneous inputs in the form of mixtures of continuous (crisp or fuzzy) numbers, linguistic information, and discrete (either ordinal or nominal) ... -
Fuzzy inputs and missing data in similarity-based heterogeneous neural networks
(Springer, 1999)
Conference report
Open AccessFuzzy heterogeneous networks are recently introduced neural network models composed of neurons of a general class whose inputs and weights are mixtures of continuous variables (crisp and/or fuzzy) with discrete quantities, ... -
A thermodynamic algorithm for feature selection
(Thomson Editores Spain, 2007)
Conference report
Open AccessThe main purpose of Feature Selection (FS) is to find a reduced subset of attributes from a data set described by a feature set. This implies a search process in the space of possible solutions, trying to optimize an ...
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