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Davide Anguita

Davide Anguita

D-Index & Metrics

Computer Science

D-Index
41
Citations
9933
World Ranking
8668
National Ranking
237

Overview

Davide Anguita is affiliated with the University of Genoa in Italy. Their research contributions span multiple topics within computer science and engineering, with a focus on artificial intelligence, computer vision, and control systems.

The scientist has published extensively in several frequent venues, including:

  • Neurocomputing
  • Cognitive Computation
  • 2022 International Joint Conference on Neural Networks (IJCNN)
  • ESANN 2021 proceedings
  • arXiv (Cornell University)

Their recent publications include the following papers:

  • "JUCS - Journal of Universal Computer Science," 2020, CINECA IRIS Institutional research information system (University of Pisa)
  • "Bridging Cognitive Models and Recommender Systems," 2020, Cognitive Computation
  • "Understanding Violin Players' Skill Level Based on Motion Capture: a Data-Driven Perspective," 2020, Cognitive Computation
  • "Optimizing Fuel Consumption in Thrust Allocation for Marine Dynamic Positioning Systems," 2021, IEEE Transactions on Automation Science and Engineering
  • "Deep fair models for complex data: Graphs labeling and explainable face recognition," 2021, Neurocomputing

Frequent co-authors working alongside Davide Anguita include:

  • Luca Oneto
  • Sandro Ridella
  • Antonio Camurri
  • Andrea Coraddu
  • Nicolò Navarin

The main fields of study for their work cover:

  • Computer Science
  • Engineering

Subfields within these areas include:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Safety Research

Their research topics reveal interests in several specialized areas evidenced by publication coverage:

  • Adversarial Robustness in Machine Learning
  • Anomaly Detection Techniques and Applications
  • Ethics and Social Impacts of AI
  • Explainable Artificial Intelligence (XAI)
  • Fault Detection and Control Systems
  • Neuroscience and Music Perception
  • Maritime Navigation and Safety

Best Publications

  • A public domain dataset for human activity recognition using smartphones

    Davide Anguita;Alessandro Ghio;Luca Oneto;Xavier Parra

  • Human activity recognition on smartphones using a multiclass hardware-friendly support vector machine

    Davide Anguita;Alessandro Ghio;Luca Oneto;Xavier Parra

  • Transition-Aware Human Activity Recognition Using Smartphones

    Jorge-L. Reyes-Ortiz;Luca Oneto;Albert Samà;Xavier Parra

  • A digital architecture for support vector machines: theory, algorithm, and FPGA implementation

    D. Anguita;A. Boni;S. Ridella

  • Big Data Analytics in the Cloud: Spark on Hadoop vs MPI/OpenMP on Beowulf

    Jorge Luis Reyes-Ortiz;Luca Oneto;Davide Anguita

  • Energy Load Forecasting Using Empirical Mode Decomposition and Support Vector Regression

    L. Ghelardoni;A. Ghio;D. Anguita

  • Energy Efficient Smartphone-Based Activity Recognition Using Fixed-Point Arithmetic

    Davide Anguita;Alessandro Ghio;Luca Oneto;Xavier Parra

  • The 'K' in K-fold Cross Validation

    Davide Anguita;Luca Ghelardoni;Alessandro Ghio;Luca Oneto

  • Vessels fuel consumption forecast and trim optimisation: A data analytics perspective

    Andrea Coraddu;Luca Oneto;Francesco Baldi;Davide Anguita

  • Machine learning approaches for improving condition-based maintenance of naval propulsion plants

    Andrea Coraddu;Luca Oneto;Alessandro Ghio;Stefano Savio

  • Condition Based Maintenance in Railway Transportation Systems Based on Big Data Streaming Analysis

    Emanuele Fumeo;Luca Oneto;Davide Anguita

  • Train Delay Prediction Systems: A Big Data Analytics Perspective ☆

    Luca Oneto;Emanuele Fumeo;Giorgio Clerico;Renzo Canepa

  • In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines

    D. Anguita;A. Ghio;L. Oneto;S. Ridella

  • Quantum optimization for training support vector machines

    Davide Anguita;Sandro Ridella;Fabio Rivieccio;Rodolfo Zunino

  • Model selection for support vector machines: Advantages and disadvantages of the Machine Learning Theory

    Davide Anguita;Alessandro Ghio;Noemi Greco;Luca Oneto

  • K-Fold Cross Validation for Error Rate Estimate in Support Vector Machines.

    Davide Anguita;Alessandro Ghio;Sandro Ridella;Dario Sterpi

  • Statistical Learning Theory and ELM for Big Social Data Analysis

    Luca Oneto;Federica Bisio;Erik Cambria;Davide Anguita

  • Theoretical and Practical Model Selection Methods for Support Vector Classifiers

    Davide Anguita;Andrea Boni;Sandro Ridella;Fabio Rivieccio

  • Dynamic Delay Predictions for Large-Scale Railway Networks: Deep and Shallow Extreme Learning Machines Tuned via Thresholdout

    Luca Oneto;Emanuele Fumeo;Giorgio Clerico;Renzo Canepa

  • Human Activity Recognition on Smartphones with Awareness of Basic Activities and Postural Transitions

    Jorge Luis Reyes-Ortiz;Jorge Luis Reyes-Ortiz;Luca Oneto;Alessandro Ghio;Albert Samà

  • Building an Underwater Wireless Sensor Network Based on Optical: Communication: Research Challenges and Current Results

    Davide Anguita;Davide Brizzolara;Giancarlo Parodi

Frequent Co-Authors

Luca Oneto
Luca Oneto University of Genoa
Matthias Rauterberg
Matthias Rauterberg Eindhoven University of Technology
Erik Cambria
Erik Cambria Nanyang Technological University
Alessandro Sperduti
Alessandro Sperduti University of Padua
Antonio Camurri
Antonio Camurri University of Genoa
Salvatore Caorsi
Salvatore Caorsi University of Pavia
Rui Calçada
Rui Calçada University of Porto
Massimo Donelli
Massimo Donelli University of Trento
Federico Delfino
Federico Delfino University of Genoa
Maurizio Valle
Maurizio Valle University of Genoa

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