Exploració per autor "Romero Merino, Enrique"
Ara es mostren els items 37-52 de 52
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On the selection of hidden neurons with heuristic search strategies for approximation
(2006)
Text en actes de congrés
Accés obertFeature Selection techniques usually follow some search strategy to select a suitable subset from a set of features. Most neural network growing algorithms perform a search with Forward Selection with the objective of ... -
On the use of pairwise distance learning for brain signal classification with limited observations
(2020-05)
Article
Accés obertThe increasing access to brain signal data using electroencephalography creates new opportunities to study electrophysiological brain activity and perform ambulatory diagnoses of neurological disorders. This work proposes ... -
On-the-fly syntheziser programming with fuzzy rule learning
(2020-08-31)
Article
Accés obertThis manuscript explores fuzzy rule learning for sound synthesizer programming within the performative practice known as live coding. In this practice, sound synthesis algorithms are programmed in real time by means of ... -
Preprocessing MRS information for classification of human brain tumours
(IGI Global, 2012-06)
Capítol de llibre
Accés restringit per política de l'editorial -
Radiomics-based assessment of optical coherence tomography angiography images for diabetic retinopathy diagnosis
(Elsevier, 2023-06)
Article
Accés obertPurpose: To evaluate the diagnostic accuracy of machine learning (ML) techniques applied to radiomic features extracted from OCT and OCT angiography (OCTA) images for diabetes mellitus (DM), diabetic retinopathy (DR), and ... -
Screening dyslexia for English using HCI measures and machine learning
(Association for Computing Machinery (ACM), 2018)
Text en actes de congrés
Accés obertMore than 10% of the population has dyslexia, and most are diagnosed only after they fail in school. This work seeks to change this through early detection via machine learning models that predict dyslexia by observing how ... -
Search strategies guided by the evidence for the selection of basis functions in regression
(Institute of Electrical and Electronics Engineers (IEEE), 2007)
Text en actes de congrés
Accés obertThis work addresses the problem of selecting a subset of basis functions for a model linear in the parameters for regression tasks. Basis functions from a set of candidates are explicitly selected with search methods coming ... -
Selection of basis functions guided by the L2 soft margin
(Springer, 2007)
Text en actes de congrés
Accés obertSupport Vector Machines (SVMs) for classification tasks produce sparse models by maximizing the margin. Two limitations of this technique are considered in this work: firstly, the number of support vectors can be large ... -
Sepsis mortality prediction with the Quotient Basis Kernel
(2014-05)
Article
Accés restringit per política de l'editorialObjective: This paper presents an algorithm to assess the risk of death in patients with sepsis. Sepsis is a common clinical syndrome in the intensive care unit (ICU) that can lead to severe sepsis, a severe state of septic ... -
Shear strength properties and collapse response of a sandy silt under generalized stress states
(American Society of Civil Engineers (ASCE), 2018)
Text en actes de congrés
Accés restringit per política de l'editorialThe paper presents preliminary results on the shear strength properties and collapse response of a compacted low-density mixture of fine sand and clayey silt in a hollow cylinder apparatus. Shear strength tests at two ... -
Stopping criteria in contrastive divergence: Alternatives to the reconstruction error
(2014)
Text en actes de congrés
Accés obertRestricted Boltzmann Machines (RBMs) are general unsupervised learning devices to ascertain generative models of data distributions. RBMs are often trained using the Contrastive Divergence learning algorithm (CD), an ... -
The impact of architecturally qualified data in deep learning methods for the automatic generation of social housing layouts
(Elsevier, 2024-02-01)
Article
Accés obertThe objective of this work is to explore the impact of the data in the automatic generation of social housing layouts with different deep learning models. The design of Social Housing is a subfield of architecture that ... -
Unraveling response to temozolomide in preclinical GL261 glioblastoma with MRI/MRSI using radiomics and signal source extraction
(Nature, 2020-11-12)
Article
Accés obertGlioblastoma is the most frequent aggressive primary brain tumor amongst human adults. Its standard treatment involves chemotherapy, for which the drug temozolomide is a common choice. These are heterogeneous and variable ... -
Using machine learning tools for protein database biocuration assistance
(Nature, 2018-07-05)
Article
Accés obertBiocuration in the omics sciences has become paramount, as research in these fields rapidly evolves towards increasingly data-dependent models. As a result, the management of web-accessible publicly-available databases ... -
Using the Fuzzy Inductive Reasoning methodology to improve coherence in algorithmic musical beat patterns
(IOS Press, 2014-10-23)
Capítol de llibre
Accés obertIn the present work, the Fuzzy Inductive Reasoning methodology (FIR) is used to improve coherence among beat patterns, structured in a musical A-B form. Patterns were generated based on a probability matrix, encoding a ... -
Weighted contrastive divergence
(2019-06)
Article
Accés obertLearning algorithms for energy based Boltzmann architectures that rely on gradient descent are in general computationally prohibitive, typically due to the exponential number of terms involved in computing the partition ...
