Data Science (DS)
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Implementing the Cumulative Difference Plot in the IOHanalyzer
(202207)The IOHanalyzer is a webbased framework that enables an easy visualization and comparison of the quality of stochastic optimization algorithms. IOHanalyzer offers several graphical and statistical tools analyze the results ... 
A Resource Sharing Game for the Freshness of Status Updates
(20210901) 
Rank aggregation for nonstationary data streams
(2022)The problem of learning over nonstationary ranking streams arises naturally, particularly in recommender systems. The rankings represent the preferences of a population, and the nonstationarity means that the distribution ... 
A twostage approach for the spatiotemporal analysis of highthroughput phenotyping data
(20220224)High throughput phenotyping (HTP) platforms and devices are increasingly used for the characterization of growth and developmental processes for large sets of plant genotypes. Such HTP data require challenging statistical ... 
A Deep Learning Approach for Generating Soft Range Information from RF Data
(20220124)Radio frequency (RF)based techniques are widely adopted for indoor localization despite the challenges in extracting sufficient information from measurements. Soft range information (SRI) offers a promising alternative ... 
Modeling latent spatiotemporal disease incidence using penalized composite link models
(20220310)Epidemiological data are frequently recorded at coarse spatiotemporal resolutions to protect confidential information or to summarize it in a compact manner. However, the detailed patterns followed by the source data, ... 
Time Series Classifier Recommendation by a MetaLearning Approach
(20220326)This work addresses time series classifier recommendation for the first time in the literature by considering several recommendation forms or metatargets: classifier accuracies, complete ranking, topM ranking, best set ... 
Analysis of Dominant Classes in Universal Adversarial Perturbations
(2022)The reasons why Deep Neural Networks are susceptible to being fooled by adversarial examples remains an open discussion. Indeed, many differ ent strategies can be employed to efficiently generate adversarial attacks, some ... 
Generalized Maximum Entropy for Supervised Classification
(202204)The maximum entropy principle advocates to evaluate events’ probabilities using a distribution that maximizes entropy among those that satisfy certain expectations’ constraints. Such principle can be generalized for ... 
PyDDRBG: A Python framework for benchmarking and evaluating static and dynamic multimodal optimization methods
(20220101)PyDDRBG is a Python framework for generating tunable test problems for static and dynamic multimodal optimization. It allows for quick and simple generation of a set of predefined problems for nonexperienced users, as ... 
Kmeans for Evolving Data Streams
(20210101)Nowadays, streaming data analysis has become a relevant area of research in machine learning. Most of the data streams available are unlabeled, and thus it is necessary to develop specific clustering techniques that take ... 
Derivation of a CostSensitive COVID19 Mortality Risk Indicator Using a Multistart Framework
(20220114)The overall global death rate for COVID19 patients has escalated to 2.13% after more than a year of worldwide spread. Despite strong research on the infection pathogenesis, the molecular mechanisms involved in a fatal ... 
A SemiSupervised Learning Approach for Ranging Error Mitigation Based on UWB Waveform
(20211230)Localization systems based on ultrawide band (UWB) measurements can have unsatisfactory performance in harsh environments due to the presence of nonlineofsight (NLOS) errors. Learningbased methods for error ... 
Deep GEMbased network for weakly supervised UWB ranging error mitigation
(20211230)Ultrawideband (UWB)based techniques, while becoming mainstream approaches for highaccurate positioning, tend to be challenged by ranging bias in harsh environments. The emerging learningbased methods for error ... 
EDA++: Estimation of Distribution Algorithms with Feasibility Conserving Mechanisms for Constrained Continuous Optimization
(20220225)Handling nonlinear constraints in continuous optimization is challenging, and finding a feasible solution is usually a difficult task. In the past few decades, various techniques have been developed to deal with linear ... 
Preference incorporation into manyobjective optimization: An Ant colony algorithm based on interval outranking
(20220301)In this paper, we enriched Ant Colony Optimization (ACO) with interval outranking to develop a novel multiobjective ACO optimizer to approach problems with many objective functions. This proposal is suitable if the ... 
A Multivariate Time Series Streaming Classifier for Predicting Hard Drive Failures [Application Notes]
(2022)Digital data storage systems such as hard drives can suffer breakdowns that cause the loss of stored data. Due to the cost of data and the damage that its loss entails, hard drive failure prediction is vital. In this ... 
Contributions to Time Series Classification: MetaLearning and Explainability
(20211116)This thesis includes 3 contributions of different types to the area of supervised time series classification, a growing field of research due to the amount of time series collected daily in a wide variety of domains. In ... 
Location Awareness in Beyond 5G Networks
(20211101)Location awareness is essential for enabling contextual services and for improving network management in 5th generation (5G) and beyond 5G (B5G) networks. This paper provides an overview of the expanding opportunities ... 
COARSEEMOA: An indicatorbased evolutionary algorithm for solving equality constrained multiobjective optimization problems
(20211201)Many realworld applications involve dealing with several conflicting objectives which need to be optimized simultaneously. Moreover, these problems may require the consideration of limitations that restrict their decision ...