Listar por autor "Guijarro-Berdiñas, Bertha"

Mostrando ítems 1-19 de 19

    • A Machine Learning Solution for Distributed Environments and Edge Computing 

      Penas-Noce, Javier; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (MDPI AG, 2019-08-09)
      [Abstract] In a society in which information is a cornerstone the exploding of data is crucial. Thinking of the Internet of Things, we need systems able to learn from massive data and, at the same time, being inexpensive ...

    • A One-Class Classification method based on Expanded Non-Convex Hulls 

      Novoa-Paradela, David; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (Elsevier, 2023)
      [Abstract]: This paper presents an intuitive, robust and efficient One-Class Classification algorithm. The method developed is called OCENCH (One-class Classification via Expanded Non-Convex Hulls) and bases its operation ...

    • A scalable decision-tree-based method to explain interactions in dyadic data 

      Eiras-Franco, Carlos; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo; Bahamonde, Antonio (Elsevier, 2019-12)
      [Abstract]: Gaining relevant insight from a dyadic dataset, which describes interactions between two entities, is an open problem that has sparked the interest of researchers and industry data scientists alike. However, ...

    • Adaptive Real-Time Method for Anomaly Detection Using Machine Learning 

      Novoa-Paradela, David; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (MDPI AG, 2020-08-20)
      [Abstract] Anomaly detection is a sub-area of machine learning that deals with the development of methods to distinguish among normal and anomalous data. Due to the frequent use of anomaly-detection systems in monitoring ...

    • An Agent-Based Model to Simulate the Spread of a Virus Based on Social Behavior and Containment Measures 

      Seijas Carpente, Manuel; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo; Rodríguez-Arias, Alejandro; Dumitru, Adina (MDPI AG, 2020-08-20)
      [Abstract] COVID-19 has brought a new normality in society. However, to avoid the situation, the virus must be stopped. There are several ways in which the governments of the world have taken action, from small measures ...

    • An Intelligent and Collaborative Multiagent System in a 3D Environment 

      Rodríguez Arias, Alejandro; Guijarro-Berdiñas, Bertha; Sánchez-Maroño, Noelia (MDPI AG, 2020-08-21)
      [Abstract] Multiagent systems (MASs) allow facing complex, heterogeneous, distributed problems difficult to solve by only one software agent. The world of video games provides problems and suitable environments for the use ...

    • Explained anomaly detection in text reviews: Can subjective scenarios be correctly evaluated? 

      Novoa-Paradela, David; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (2024-07)
      In the current landscape, user opinions exert an unprecedented influence on the trajectory of companies. In the field of online review platforms, these opinions, transmitted through text reviews and numerical ratings, ...

    • Fast deep autoencoder for federated learning 

      Novoa-Paradela, David; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (Elsevier Ltd, 2023-11)
      [Abstract]: This paper presents a novel, fast and privacy preserving implementation of deep autoencoders. DAEF (Deep AutoEncoder for Federated learning), unlike traditional neural networks, trains a deep autoencoder network ...

    • Fast Distributed kNN Graph Construction Using Auto-tuned Locality-sensitive Hashing 

      Eiras-Franco, Carlos; Martínez Rego, David; Kanthan, Leslie; Piñeiro, César; Bahamonde, Antonio; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo (Association for Computing Machinery, 2020)
      [Abstract]: The k-nearest-neighbors (kNN) graph is a popular and powerful data structure that is used in various areas of Data Science, but the high computational cost of obtaining it hinders its use on large datasets. ...

    • FedHEONN: Federated and homomorphically encrypted learning method for one-layer neural networks 

      Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha; Hernández-Pereira, Elena; Pérez-Sánchez, Beatriz (Elsevier B.V., 2023)
      [Abstract]: Federated learning (FL) is a distributed approach to developing collaborative learning models from decentralized data. This is relevant to many real applications, such as in the field of the Internet of Things, ...

    • How Agent-based modeling can help to foster sustainability projects 

      Sánchez-Maroño, Noelia; Rodríguez Arias, Alejandro; Dumitru, Adina; Lema-Blanco, Isabel; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo (Elsevier, 2022)
      [Abstract] The Sustainable Development Goals (SDGs) adopted by the United Nations require relevant social changes that sometimes involve the development of innovative projects that cause rejection and confrontation. ...

    • Interpretable market segmentation on high dimension data 

      Eiras-Franco, Carlos; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo; Bahamonde, Antonio (M D P I AG, 2018-09-17)
      [Abstract] Obtaining relevant information from the vast amount of data generated by interactions in a market or, in general, from a dyadic dataset, is a broad problem of great interest both for industry and academia. Also, ...

    • Large scale anomaly detection in mixed numerical and categorical input spaces 

      Eiras-Franco, Carlos; Martínez Rego, David; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo; Bahamonde, Antonio (Elsevier, 2019)
      [Abstract]: This work presents the ADMNC method, designed to tackle anomaly detection for large-scale problems with a mixture of categorical and numerical input variables. A flexible parametric probability measure is ...

    • Machine Learning Techniques to Predict Different Levels of Hospital Care of CoVid-19 

      Hernández-Pereira, Elena; Fontenla-Romero, Óscar; Bolón-Canedo, Verónica; Cancela, Brais; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo (Springer, 2022)
      [Abstract] In this study, we analyze the capability of several state of the art machine learning methods to predict whether patients diagnosed with CoVid-19 (CoronaVirus disease 2019) will need different levels of hospital ...

    • SARDAM: Service Assistant Robot for Daily Activity Monitoring 

      Meizoso Lamas, Celtia; Bellas, Francisco; Guijarro-Berdiñas, Bertha (MDPI, 2020)
      [Abstract] In this work, we propose an autonomous monitoring system for the daily routine of an elderly person. SARDAM (Service Assistant Robot for Daily Activity Monitoring), which is the name of this system, uses a ...

    • Scalable Feature Selection Using ReliefF Aided by Locality-Sensitive Hashing 

      Eiras-Franco, Carlos; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo; Bahamonde, Antonio (Wiley, 2021)
      [Abstract] Feature selection algorithms, such as ReliefF, are very important for processing high-dimensionality data sets. However, widespread use of popular and effective such algorithms is limited by their computational ...

    • Simulating the Role of Norms in Processes of Social Innovation: Three Case Studies 

      Jager, Wander; Guijarro-Berdiñas, Bertha; Bouman, Loes; Antosz, Patrycja; Alonso-Betanzos, Amparo; Salt, Douglas; Polhill, J. Gary; Rodríguez Arias, Alejandro; Sánchez-Maroño, Noelia (SimSoc Consortium, 2024-01)
      [Absctract]: Norms and values are critical drivers in social innovation processes, such as community projects on sustainable energy. Simulating such processes could help uncover conditions that support these social ...

    • Simulation of Virus Propagation and Acceptance of Socio-Sanitary Measures Through an Intelligent Model 

      García-Paz, Daniel J.; Alonso-Betanzos, Amparo; Guijarro-Berdiñas, Bertha; Rodríguez-Arias, Alejandro (Universidade da Coruña, Servizo de Publicacións, 2023)
      [Abstract] During the most critical moments of the SARS-COV-2 pandemic, various containment measures were enacted to hinder the virus’s spread and mitigate its impact. This work focuses on studying the impact of the ...

    • Sustainable personalisation and explainability in Dyadic Data Systems 

      Paz Ruza, Jorge; Eiras-Franco, Carlos; Guijarro-Berdiñas, Bertha; Alonso-Betanzos, Amparo (2022)
      [Abstract]: Systems that rely on dyadic data, which relate entities of two types together, have become ubiquitously used in fields such as media services, tourism business, e-commerce, and others. However, these systems ...