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Santiago Mazuelas Franco

BCAM Researcher

T +34 946 567 842
F +34 946 567 843
E smazuelas@bcamath.org

Information of interest

  • Crowd-Centric Counting via Unsupervised Learning 

    Morselli, F.; Bartoletti, S.; Mazuelas, S.Autoridad BCAM; Win, M.; Conti, A. (2019-07-11)
    Counting targets (people or things) within a moni-tored area is an important task in emerging wireless applications,including those for smart environments, safety, and security.Conventional device-free radio-based ...
  • General supervision via probabilistic transformations 

    Mazuelas, S.Autoridad BCAM; Pérez, A.Autoridad BCAM (2020-08-01)
    Different types of training data have led to numerous schemes for supervised classification. Current learning techniques are tailored to one specific scheme and cannot handle general ensembles of training samples. This ...
  • Generalized Maximum Entropy for Supervised Classification 

    Mazuelas, S.Autoridad BCAM; Shen, Y.; Pérez, A.Autoridad BCAM (2022-04)
    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 ...
  • Location Awareness in Beyond 5G Networks 

    Conti, A.; Morselli, F.; Liu, Z.; Bartoletti, S.; Mazuelas, S.Autoridad BCAM; Lindsey, W.C.; Win, M.Z. (2021-11-01)
    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 ...
  • Minimax Classification with 0-1 Loss and Performance Guarantees 

    Mazuelas, S.Autoridad BCAM; Zanoni, A.; Pérez, A.Autoridad BCAM (2020-12-01)
    Supervised classification techniques use training samples to find classification rules with small expected 0-1 loss. Conventional methods achieve efficient learning and out-of-sample generalization by minimizing surrogate ...
  • Probabilistic Load Forecasting Based on Adaptive Online Learning 

    Álvarez, V.Autoridad BCAM; Mazuelas, S.Autoridad BCAM; Lozano, J.A.Autoridad BCAM (2020)
    Load forecasting is crucial for multiple energy management tasks such as scheduling generation capacity, planning supply and demand, and minimizing energy trade costs. Such relevance has increased even more in recent ...
  • Soft information for localization-of-things 

    Conti, A.; Mazuelas, S.Autoridad BCAM; Bartoletti, S.; Lindsey, W.C; Win, M. (2019-11-01)
    Location awareness is vital for emerging Internetof- Things applications and opens a new era for Localizationof- Things. This paper first reviews the classical localization techniques based on single-value metrics, such ...
  • Soft range information for network localization 

    Mazuelas, S.Autoridad BCAM; Conti, A.; Allen, J.C.; Win, M.Z. (2018-06-15)
    The demand for accurate localization in complex environments continues to increase despite the difficulty in extracting positional information from measurements. Conventional range-based localization approaches rely on ...
  • Spatiotemporal information coupling in network navigation 

    Mazuelas, S.Autoridad BCAM; Shen, Y.; Win, Z. (2018-12)
    Network navigation, encompassing both spatial and temporal cooperation to locate mobile agents, is a key enabler for numerous emerging location-based applications. In such cooperative networks, the positional information ...

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