Word n-gram attention models for sentence similarity and inference
Authors: Iñigo Lopez-Gazpio,Eneko Agirre,Montse Maritxalar,Mirella Lapata
Semantic Textual Similarity and Natural Language Inference are two popular natural language understanding tasks used to benchmark sentence representation models where two sentences are paired. In such tasks sentences are represented as bag of words, sequences, trees or convolutions, but the…
Elsevier BV
A Question of Trust: Statistical Characterization of Long-Term Traffic Estimations for their Improved Actionability
Authors: Javier Del Ser,Urtats Etxegarai,Esther Villar-Rodriguez,Ibai Laña,Izaskun Oregi
Actionability is a key aspect of research advances achieved in diverse fields, as it determines whether new developments are useful in practice for expert users. Intelligent Transport Systems (ITS) are among such fields due to the highly applied set of knowledge areas lying at their core, with some…
IEEE
A reproducible survey on word embeddings and ontology-based methods for word similarity: Linear combinations outperform the state of the art
Authors: Eneko Agirre,Mohamed Ben Aouicha,Josu Goikoetxea,Juan J. Lastra-Díaz,Mohamed Ali Hadj Taieb,Ana García-Serrano
Abstract Human similarity and relatedness judgements between concepts underlie most of cognitive capabilities, such as categorisation, memory, decision-making and reasoning. For this reason, the proposal of methods for the estimation of the degree of similarity and relatedness between words and…
Elsevier BV
Road Traffic Forecasting using Stacking Ensembles of Echo State Networks
Authors: Miren Nekane Bilbao,Eleni I. Vlahogianni,Javier Del Ser,Ibai Laña
Road traffic forecasting is arguably one of the practical applications related to Intelligent Transportation Systems where Machine Learning models have impacted most significantly in recent years. The advent of increasingly sophisticated supervised learning methods to capture and generalize complex…
IEEE
What Lies Beneath: A Note on the Explainability of Black-box Machine Learning Models for Road Traffic Forecasting
Authors: Ibai Laña,Javier Del Ser,Alejandro Barredo-Arrieta
Traffic flow forecasting is widely regarded as an essential gear in the complex machinery underneath Intelligent Transport Systems, being a critical component of avant-garde Automated Traffic Management Systems. Research in this area has stimulated a vibrant activity, yielding a plethora of new…
IEEE
Reproducibility dataset for a large experimental survey on word embeddings and ontology-based methods for word similarity
Authors: Juan J. Lastra-Díaz,Josu Goikoetxea,Mohamed Ali Hadj Taieb,Ana García-Serrano,Mohamed Ben Aouicha,Eneko Agirre
This data article introduces a reproducibility dataset with the aim of allowing the exact replication of all experiments, results and data tables introduced in our companion paper (Lastra-Díaz et al., 2019), which introduces the largest experimental survey on ontology-based semantic similarity…
Elsevier BV
Characterisation of Martian dust aerosol phase function from sky radiance measurements by MSL engineering cameras
Authors: Santiago Pérez-Hoyos,Agustín Sánchez-Lavega,H. Chen-Chen
Dust is the main driver of Mars' atmospheric variability. The determination of Martian dust aerosol properties is of high relevance for radiative modelling and calculating its weather forcing. In particular, the light scattering behaviour at intermediate and large scattering angles can provide…
Elsevier BV
Reducing variability in the cost of energy of ocean energy arrays
Authors: Topper, Mathew B.R.,Nava, Vincenzo,Collin, Adam J.,Bould, David,Ferri, Francesco,Olson, Sterling S.,Dallman, Ann R.,Roberts, Jesse D.,Ruiz-Minguela, Pablo,Jeffrey, Henry F.
Variability in the predicted cost of energy of an ocean energy converter array is more substantial than for other forms of energy generation, due to the combined stochastic action of weather conditions and failures. If the variability is great enough, then this may influence future financial…
Elsevier BV
Capnography: A support tool for the detection of return of spontaneous circulation in out-of-hospital cardiac arrest
Authors: Andoni Elola,Elisabete Aramendi,Unai Irusta,Erik Alonso,Yuanzheng Lu,Mary P. Chang,Pamela Owens,Ahamed H. Idris
Automated detection of return of spontaneous circulation (ROSC) is still an unsolved problem during cardiac arrest. Current guidelines recommend the use of capnography, but most automatic methods are based on the analysis of the ECG and thoracic impedance (TI) signals. This study analysed the added…
Elsevier BV
Association of ventilation with outcomes from out-of-hospital cardiac arrest
Authors: Mary P. Chang,Yuanzheng Lu,Brian Leroux,Elisabete Aramendi Ecenarro,Pamela Owens,Henry E. Wang,Ahamed H. Idris
Abstract Aim of study To determine the association between bioimpedence-detected ventilation and out-of-hospital cardiac arrest (OHCA) outcomes. Methods This is a retrospective, observational study of 560 OHCA patients from the Dallas-Fort Worth site enrolled in the Resuscitation Outcomes…
Elsevier BV
Bio-inspired computation: Where we stand and what's next
Authors: Xin-She Yang,Eneko Osaba,Swagatam Das,Javier Del Ser,Javier Del Ser,Francisco Herrera,David Camacho,Ponnuthurai Nagaratnam Suganthan,Carlos A. Coello Coello,Daniel Molina,Sancho Salcedo-Sanz
In recent years, the research community has witnessed an explosion of literature dealing with the adaptation of behavioral patterns and social phenomena observed in nature towards efficiently solving complex computational tasks. This trend has been especially dramatic in what relates to…
Elsevier BV
Nature-inspired metaheuristics for optimizing information dissemination in vehicular networks
Authors: Antonio D. Masegosa,Juan S. Angarita-Zapata,Javier Del Ser,Eneko Osaba,Ibai Laña
Connected vehicles are revolutionizing the way in which transport and mobility are conceived. The main technology behind is the so-called Vehicular Ad-Hoc Networks (VANETs), which are communication networks that connect vehicles and facilitate various services. Usually these services require a…
ACM
Bayesian performance analysis for black-box optimization benchmarking
Authors: Calvo, Borja,Shir, Ofer,Ceberio, Josu,Doerr, Carola,Wang, Hao,Back, Thomas,Lozano, Jose
International audience; The most commonly used statistics in Evolutionary Computation (EC) are of the Wilcoxon-Mann-Whitney-test type, in its either paired or non-paired version. However, using such statistics for drawing performance comparisons has several known drawbacks. At the same time,…
ACM
Computing rational border curves of melanoma and other skin lesions from medical images with bat algorithm
Authors: Akemi Gálvez,Iztok Fister,Eneko Osaba,Iztok Fister,Javier Del Ser,Andrés Iglesias
Border detection of melanoma and other skin lesions from images is an important step in the medical image processing pipeline. Although this task is typically carried out manually by the dermatologists, some recent papers have applied evolutionary computation techniques to automate this process.…
ACM
Discovering dependencies among mined association rules with population-based metaheuristics
Authors: Iztok Fister,Akemi Galvez,Eneko Osaba,Javier Del Ser,Andres Iglesias,Iztok Fister
Stochastic population-based nature-inspired metaheuristics have been proven as a robust tool for mining association rules. These algorithms are very scalable, as well as very fast compared with some deterministic ones that search for solutions exhaustively. Typically, algorithms for association…
ACM
Sentiment analysis with genetically evolved gaussian kernels
Authors: Roman, I.,Santana, R.,Mendiburu, A.,Lozano, J.A.
Sentiment analysis consists of evaluating opinions or statements from the analysis of text. Among the methods used to estimate the degree in which a text expresses a given sentiment, are those based on Gaussian Processes. However, traditional Gaussian Processes methods use a predefined kernel with…
ACM
Combining bio-inspired meta-heuristics and novelty search for community detection over evolving graph streams
Authors: Ángel Panizo,Eneko Osaba,Akemi Gálvez,Javier Del Ser,David Camacho,Andrés Iglesias
Finding communities of interrelated nodes is a learning task that often holds in problems that can be modeled as a graph. In any case, detecting an optimal partition in a graph is highly time-consuming and complex. For this reason, the implementation of search-based metaheuristics arises as an…
ACM
Hybridizing differential evolution and novelty search for multimodal optimization problems
Authors: Aritz D. Martinez,Eneko Osaba,Izaskun Oregi,Iztok Fister,Iztok Fister,Javier Del Ser
Multimodal optimization has shown to be a complex paradigm underneath real-world problems arising in many practical applications, with particular prevalence in physics-related domains. Among them, a plethora of cases within the computational design of aerospace structures can be modeled as a…
ACM
A Dialogue-Act Taxonomy for a Virtual Coach Designed to Improve the Life of Elderly
Authors: César Montenegro,Asier López Zorrilla,Javier Mikel Olaso,Roberto Santana,Raquel Justo,Jose A. Lozano,María Inés Torres
This paper presents a dialogue act taxonomy designed for the development of a conversational agent for elderly. The main goal of this conversational agent is to improve life quality of the user by means of coaching sessions in different topics. In contrast to other approaches such as task-oriented…
MDPI AG
A Hardy-type inequality and some spectral characterizations for the Dirac–Coulomb operator
Authors: Fabio Pizzichillo,Biagio Cassano,Luis Vega,Luis Vega
We prove a sharp Hardy-type inequality for the Dirac operator. We exploit this inequality to obtain spectral properties of the Dirac operator perturbed with Hermitian matrix-valued potentials $\mathbf V$ of Coulomb type: we characterise its eigenvalues in terms of the Birman-Schwinger principle and…
Springer Science and Business Media LLC
A Robust Machine Learning Architecture for a Reliable ECG Rhythm Analysis during CPR
Authors: Jo Kramer-Johansen,Andoni Elola,Iraia Isasi,Trygve Eftestøl,Lars Wik,Elisabete Aramendi,Unai Irusta
Chest compressions delivered during cardiopulmonary resuscitation (CPR) induce artifacts in the ECG that may make the shock advice algorithms (SAA) of defibrillators inaccurate. There is evidence that methods consisting of adaptive filters that remove the CPR artifact followed by machine learning (…
IEEE
ECG-based Random Forest Classifier for Cardiac Arrest Rhythms
Authors: Elisabete Aramendi,Iraia Isasi,Mikel Olabarria,Javier Del Ser,Carlos Corcuera,Andima Larrea,Unai Irusta,Eric L. Manibardo,Jose Veintemillas
Rhythm annotation of out-of-hospital cardiac episodes (OHCA) is key for a better understanding of the interplay between resuscitation therapy and OHCA patient outcome. OHCA rhythms are classified in five categories, asystole (AS), pulseless electrical activity (PEA), pulsed rhythms (PR),…
IEEE