Now showing items 21-40 of 1033

    • A genetic attack against machine learning classifiers to steal biometric actigraphy profiles from health related sensor data 

      Garcia Ceja, Enrique; Morin, Brice; Aguilar Rivera, Anton; Riegler, Michael Alexander (Springer, 2020)
      Article
      Open Access
      In this work, we propose the use of a genetic-algorithm-based attack against machine learning classifiers with the aim of ‘stealing’ users’ biometric actigraphy profiles from health related sensor data. The target ...
    • A highly parameterizable framework for Conditional Restricted Boltzmann Machine based workloads accelerated with FPGAs and OpenCL 

      Jaksic, Zoran; Cadenelli, Nicola; Buchaca Prats, David; Polo Bardés, Jordà; Berral García, Josep Lluís; Carrera Pérez, David (Elsevier, 2020-03-01)
      Article
      Open Access
      Conditional Restricted Boltzmann Machine (CRBM) is a promising candidate for a multidimensional system modeling that can learn a probability distribution over a set of data. It is a specific type of an artificial neural ...
    • A Human Shape-Motion Predictor with Deep Learning 

      Romero Mérida, Antonio (Universitat Politècnica de Catalunya, 2019-04-24)
      Master thesis
      Open Access
      The objective of this work is to obtain an end-to-end solution which predicts human motion and shape from a given video by extracting its pose in the Wild. Given incomplete human motion sequences our goal is to predict and ...
    • A Hybrid Computer-aided-diagnosis System for Prediction of Breast Cancer Recurrence (HPBCR) using optimized ensemble learning 

      Mohebian, Mohammad Reza; Marateb, Hamid Reza; Mansourian, Marjan; Mañanas Villanueva, Miguel Ángel; Mokarian, Fariborz (Elsevier, 2016-12-06)
      Article
      Restricted access - publisher's policy
      Cancer is a collection of diseases that involves growing abnormal cells with the potential to invade or spread tothe body. Breast cancer is the second leading cause of cancer death among women. A method for 5-year breastcancer ...
    • A learning system for adjustment processes based on human sensory perceptions 

      Ruiz Vegas, Francisco Javier; Agell Jané, Núria; Angulo Bahón, Cecilio; Sánchez Soler, Monica (2018-12-01)
      Article
      Open Access
      Creating, designing and adjusting products are essential decision processes underlying creative industries, such as painting, perfume, food and beverage industries. These processes require the participation and continuous ...
    • A lightweight perception module for planning purposes 

      Ud Din, Muhayy; Rosell Gratacòs, Jan; Bukhari, Sohail; Ahmad, Mansoor; Qazi, Wajahat Mahmood (Institute of Electrical and Electronics Engineers (IEEE), 2020)
      Conference lecture
      Open Access
      Sensing is an essential component for robots to perform the manipulation tasks in real environments. This study proposes a lightweight deep-learning-based sensing modules which allows the robots to automatically model the ...
    • A lower bound for learning distributions generated by probabilistic automata 

      Balle Pigem, Borja de; Castro Rabal, Jorge; Gavaldà Mestre, Ricard (Springer, 2010)
      Conference report
      Open Access
      Known algorithms for learning PDFA can only be shown to run in time polynomial in the so-called distinguishability μ of the target machine, besides the number of states and the usual accuracy and confidence parameters. ...
    • A machine learning approach for layout inference in spreadsheets 

      Koci, Elvis; Thiele, Maik; Romero Moral, Óscar; Lehner, Wolfgang (SciTePress, 2016)
      Conference report
      Open Access
      Spreadsheet applications are one of the most used tools for content generation and presentation in industry and the Web. In spite of this success, there does not exist a comprehensive approach to automatically extract and ...
    • A machine learning approach to calculate the dropout risk factor in a children's programming school 

      Horta Bartomeu, Raquel (Universitat Politècnica de Catalunya, 2019-01-29)
      Bachelor thesis
      Restricted access - confidentiality agreement
    • A machine learning approach to stock screening with fundamental analysis 

      Alvarez Vecino, Pol (Universitat Politècnica de Catalunya, 2019-04-15)
      Master thesis
      Open Access
      We present HPC.FASSR, a High-Performance Computation Fundamental Analysis Stock Screener and Ranker to compare many ML models and the criteria of famous Benjamin Graham for stock investing using fundamental data. FASSR is ...
    • A machine learning approach to the identification of encrypted web traffic 

      Marías Pérez, Rubén (Universitat Politècnica de Catalunya, 2017-06-29)
      Bachelor thesis
      Restricted access - confidentiality agreement
    • A machine learning enabled network planning tool 

      Moysen Cortes, Jessica; Giupponi, Lorenza; Mangues Bafalluy, Josep (Institute of Electrical and Electronics Engineers (IEEE), 2016)
      Conference report
      Restricted access - publisher's policy
      In the coming years, planning future mobile networks will be infinitely more complex than nowadays. Future networks are expected to present multiple Network Management (NM) challenges to operators, such as managing network ...
    • A machine learning methodology for structural damage classification in structural health monitoring 

      Pozo Montero, Francesc; Tibaduiza Burgos, Diego Alexander; Anaya Vejar, Maribel; Vitola Oyaga, Jaime (2017)
      Conference report
      Restricted access - publisher's policy
      One of the goals of structural health monitoring (SHM) applications is to determine the presence and the severity of a damage. In some cases, this is an element to forecast the behaviour and take decisions to allocate ...
    • A machine learning pipeline for supporting differentiation of glioblastomas from single brain metastases 

      Mocioiu, Victor; de Barros, Nuno M. Pedrosa; Ortega Martorell, Sandra; Slotboom, Johannes; Knecht, Urspeter; Arús, Carles; Vellido Alcacena, Alfredo; Julià Sapé, Margarida (I6doc.com, 2016)
      Conference report
      Open Access
      Machine learning has provided, over the last decades, tools for knowledge extraction in complex medical domains. Most of these tools, though, are ad hoc solutions and lack the systematic approach that would be required to ...
    • A machine learning workflow for hurricane prediction 

      Kahira, Albert; Bautista Gomez, Leonardo; Badia Sala, Rosa Maria (Barcelona Supercomputing Center, 2018-04-24)
      Conference report
      Open Access
    • A methodological approach for algorithmic composition systems' parameter spaces aesthetic exploration 

      Paz Ortiz, Iván; Nebot Castells, M. Àngela; Romero Merino, Enrique; Múgica Álvarez, Francisco; Vellido Alcacena, Alfredo (Institute of Electrical and Electronics Engineers (IEEE), 2017)
      Conference lecture
      Open Access
      Algorithmic composition is the process of creating musical material by means of formal methods. As a consequence of its design, algorithmic composition systems are (explicitly or implicitly) described in terms of parameters. ...
    • A methodology for developing knowledge-based systems 

      Castro Peña, Juan Luis; Castro Sánchez, José Jesús; Espín Andrade, Rafael Alejandro; Zurita López, José Manuel (Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica, 1998)
      Article
      Open Access
      This paper presents a methodology for developing fuzzy knowledge based systems (KBS), which permits a complete automatization. This methodology will be useful for approaching more complex problems that those in which machine ...
    • A mobile network planning tool based on data analytics 

      Moysen Cortes, Jessica; Giupponi, Lorenza; Mangues Bafalluy, Josep (HINDAWI, 2017-02-05)
      Article
      Open Access
      Planning future mobile networks entails multiple challenges due to the high complexity of the network to be managed. Beyond 4G and 5G networks are expected to be characterized by a high densification of nodes and heterogeneity ...
    • A multi-scale smoothing kernel for measuring time-series similarity 

      Troncoso, Alicia; Arias Vicente, Marta; Riquelme Santos, José Cristóbal (2015-11-01)
      Article
      Open Access
      In this paper a kernel for time-series data is introduced so that it can be used for any data mining task that relies on a similarity or distance metric. The main idea of our kernel is that it should recognize as highly ...
    • A multiscale method for periodic structures using domain decomposition and ECM-hyperreduction 

      Hernández Ortega, Joaquín Alberto (2020-08-15)
      Article
      Restricted access - publisher's policy
      This paper presents a nonlinear multiscale approach for periodic structures in the quasi-static, small strain regime. The approach consists in combining a domain decomposition method in which interface conditions are ...