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Publications 

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International Journals
  1. L. Oneto, A. Ghio, S. Ridella, D. Anguita, 
    Learning Resource-Aware Models for Mobile Devices: from Regularization to Energy Efficiency, 
    Neurocomputing, 
    (In Press)

  2. L. Oneto, A. Ghio, S. Ridella, D. Anguita, 
    Fully Empirical and Data-Dependent Stability-Based Bounds, 
    IEEE Transactions on Cybernetics, 
    (In Press)

  3. A. Coraddu, L. Oneto, A. Ghio, S. Savio, D. Anguita, M. Figari, 
    Machine Learning Approaches for Improving Condition–Based Maintenance of Naval Propulsion Plants, 
    Journal of Engineering for the Maritime Environment, 
    DOI: 10.1177/1475090214540874
    (In Press)

  4. D. Anguita, A. Ghio, L. Oneto, S. Ridella, 
    A Deep Connection Between the Vapnik–Chervonenkis Entropy and the Rademacher Complexity, 
    IEEE Transactions on Neural Networks and Learning Systems,
    Vol. 25, n. 12, pp. 2202-2211, 2014. 
    ISSN: 2162-237X, DOI: 10.1109/TNNLS.2014.2307359

  5. D. Anguita, A. Ghio, L. Oneto, S. Ridella,
    Unlabeled Patterns to Tighten Rademacher Complexity Error Bounds for Kernel Classifiers,
    Pattern Recognition Letters,
    Vol. 37, pp. 210-219, 2014.
    ISSN: 0167-8655, DOI: 10.1016/j.patrec.2013.04.027

  6. L. Oneto, A. Ghio, D. Anguita, S. Ridella,
    An improved analysis of the Rademacher data-dependent bound using its self bounding property,
    Neural Networks,
    Vol. 44, pp. 107-111, 2013. 
    ISSN: 0893-6080, DOI: 10.1016/j.neunet.2013.03.017

  7. D. Anguita, L. Ghelardoni, A. Ghio, S. Ridella
    A Survey of Old and New Results for the Test Error Estimation of a Classifier
    Journal of Artificial Intelligence and Soft Computing Research
    Vol. 3, n. 4, 2013.
    (in press) ISBN: 978-83-62916-14-6.

  8. D. Anguita, A. Ghio, L. Oneto, X. Parra, J. L. Reyes-Ortiz,
    Energy Efficient Smartphone-Based Activity Recognition using Fixed-Point Arithmetic,
    Journal of Universal Computer Science,
    Vol. 19, N. 6, pp. 1295-1314, 2013.
    DOI: 10.3217/jucs-019-09-1295.

  9. L. Ghelardoni, A. Ghio, D. Anguita
    Energy Load Forecasting Using Empirical Mode Decomposition and Support Vector Regression
    IEEE Transactions on Smart Grid
    Vol. 4, N. 1, pp. 549-556, 2013,
    ISSN: 1949-3053, DOI: 10.1109/TSG.2012.2235089 

  10. D. Anguita, A. Ghio, L. Oneto, S. Ridella,
    In-Sample Model Selection for Trimmed Hinge Loss Support Vector Machine, 
    Neural Processing Letters,
    Vol. 36, No. 3, pp. 275-283, 2012,
    ISSN: 1370-4621, DOI: 10.1007/s11063-012-9235-z

  11. D. Anguita, A. Ghio, L. Oneto, S. Ridella, 
    In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines, 
    IEEE Transactions on Neural Networks and Learning Systems, 
    Vol. 23, No. 9, pp. 1390-1406, 2012.
    ISSN: 2162-237X, DOI: 10.1109/TNNLS.2012.2202401

  12. D. Anguita, A. Ghio, S. Ridella,
    Maximal Discrepancy for Support Vector Machines
    Neurocomputing,
    Vol. 74, N. 9, pp. 1436-1443, 2011,
    ISSN: 0925-2312, DOI: 10.1016/j.neucom.2010.12.009

  13. D. Anguita, L. Carlino, A. Ghio, S. Ridella,
    A FPGA Core Generator for Embedded Classification Systems
    Journal of Circuits, Systems and Computers,
    Vol. 20, N. 2, pp. 263-282, 2011,
    DOI: 10.1142/S0218126611007244

  14. D. Anguita, A. Ghio, S. Pischiutta, S. Ridella,
    A support vector machine with integer parameters
    Neurocomputing,
    Vol. 72, N. 1-3, pp. 480-489, 2008,
    ISSN: 0925-2312, DOI: 10.1016/j.neucom.2007.12.006

Published International Conferences
  1. A. Coraddu, L. Oneto, S. Savio, M. Figari, A. Ghio, D. Anguita,
    A Public Domain Dataset for Wear Forecasting of Naval Assets for Condition-Based Maintenance Applications,
    Proc. of the International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles
    (in press), Aachen, Germany, 3-5 March 2015.

  2. L. Oneto, J. L. Reyes-Ortiz, A. Ghio, S. Ridella, D. Anguita,
    Out-of-Sample Error Estimation: the Blessing of High Dimensionality,
    Proc. of the IEEE International Conference on Data Mining (ICDM) Workshops
    (in press), Shenzen, China, 14-17 Dec. 2014.

  3. M. Vahdat, L. Oneto, A. Ghio, G. Donzellini, D. Anguita,
    A Learning Analytics Methodology to Profile Students Behavior and Explore Interactions with Deeds Simulator,
    Ninth European Conference on Technology Enhanced Learning (EC-TEL) 
    pp. 596-597, Graz, Austria, 16-19 Sep. 2014.
    ISBN: 978-3-319-11199-5, DOI: 10.1007/978-3-319-11200-8_87

  4. J. L. Reyes-Ortiz, L. Oneto, A. Ghio, A. Sama, D. Anguita, X. Parra,
    Human Activity Recognition on Smartphones With Awareness of Basic Activities and Postural Transitions,
    24nd Int. Conf. on Artificial Neural Networks (ICANN) 
    pp. 177-184, Hamburg, Germany, 15–19 Sep. 2014.
    ISBN: 978-3-319-11178-0, DOI: 10.1007/978-3-319-11179-7_23

  5. A. Coraddu, M. Figari, A. Ghio, L. Oneto, S. Savio,
    A Sustainability Analytics Matlab Tool to Predict Ship Energy Consumption,
    International Conference on Computer Applications and Information Technology in the Maritime Industries (COMPIT) 
    pp. 350-364, Redworth, United Kingdom, 12-14 May 2014.
    ISBN: 978-3-89220-672-9

  6. D. Anguita, A. Ghio, L. Oneto, S. Ridella,
    Smartphone Battery Saving by Bit-Based Hypothesis Spaces and Local Rademacher Complexities,
    IEEE Int. Joint Conference on Neural Networks (IJCNN) 
    pp. 3916-3921, Beijin, China, 6-11 Jul. 2014.
    ISBN: 978-1-4799-6627-1, DOI: 10.1109/IJCNN.2014.6889482

  7. A. Ghio, L. Oneto,
    Byte The Bullet: Learning on Real-World Computing Architectures,
    22th European Symposium on Artificial Neural Networks, 
    Computational Intelligence and Machine Learning (ESANN),
    pp. 71-80, Bruges, Belgium, 23-25 Apr. 2014.
    ISBN: 978-2-87419-095-7

  8. D. Anguita, A. Ghio, L. Oneto, S. Ridella,
    Learning with Few Bits on Small--Scale Devices: from Regularization to Energy Efficiency,
    22th European Symposium on Artificial Neural Networks, 
    Computational Intelligence and Machine Learning (ESANN),
    pp. 81-86, Bruges, Belgium, 23-25 Apr. 2014.
    ISBN: 978-2-87419-095-7

  9. D. Anguita, A. Ghio, L. Oneto, X. Parra, J. L. Reyes-Ortiz,
    Training Computationally Efficient Smartphone-Based Human Activity Recognition Models,
    23nd Int. Conf. on Artificial Neural Networks (ICANN), 
    pp. 426-433, Sofia, Bulgaria, 10-13 Sept. 2013.
    ISBN: 978-3-642-40727-7, DOI: 10.1007/978-3-642-40728-4_54.

  10. D. Anguita, A. Ghio, L. Oneto, J. L. Reyes-Ortiz, S. Ridella,
    A Novel Procedure for Training L1-L2 Support Vector Machine Classifiers,
    23nd Int. Conf. on Artificial Neural Networks (ICANN), 
    pp. 434-441, Sofia, Bulgaria, 10-13 Sept. 2013.
    ISBN: 978-3-642-40727-7, DOI: 10.1007/978-3-642-40728-4_55.

  11. D. Anguita, A. Ghio, I. A. LawalL. Oneto,
    A Heuristic Approach to Model Selection for Online Support Vector Machines,
    International Workshop on Advances in Regularization, Optimization, Kernel Methods and Support Vector Machines: theory and applications.
    pp. 77-78, Leuven, Belgium, July 8 - 10, 2013.
    ISBN: 978-94-6018-700-1.

  12. D. Anguita, A. Ghio, L. Oneto, S. Ridella, 
    Some Results About the Vapnik-Chervonenkis Entropy and the Rademacher Complexity, 
    IEEE Int. Joint Conference on Neural Networks (IJCNN),
    pp. 1-8, Dallas, TX, USA, 4 - 9 Aug. 2013. 
    ISBN: 978-1-4673-6128-6, DOI: 10.1109/IJCNN.2013.6706943.

  13. D. Anguita, A. Ghio, L. Oneto, S. Ridella, 
    A Support Vector Machine Classifier from a Bit-Constrained, Sparse and Localized Hypothesis Space,
    IEEE Int. Joint Conference on Neural Networks (IJCNN),
    pp. 1-10, Dallas, TX, USA, 4 - 9 Aug. 2013. 
    ISBN: 978-1-4673-6128-6, DOI: 10.1109/IJCNN.2013.6706868.

  14. D. Anguita, A. Ghio, L. Oneto, S. Ridella, 
    A Learning Machine with a Bit-Based Hypothesis Space, 
    21th European Symposium on Artificial Neural Networks, 
    Computational Intelligence and Machine Learning (ESANN),
    pp. 467-472, Bruges, Belgium, 24-26 Apr. 2013.
    ISBN: 978-2-87419-081-0.

  15. J.L. Reyes-Ortiz, A. Ghio, D. Anguita, X. Parra, J. Cabestany, A. Català, 
    Human Activity and Motion Disorder Recognition: Towards Smarter Interactive Cognitive Environments, 
    21th European Symposium on Artificial Neural Networks, 
    Computational Intelligence and Machine Learning (ESANN),
    pp. 403-412, Bruges, Belgium, 24-26 Apr. 2013.
    ISBN: 978-2-87419-081-0.

  16. D. Anguita, A. Ghio, L. Oneto, X. Parra, J. L. Reyes-Ortiz,
    A Public Domain Dataset for Human Activity Recognition using Smartphones, 
    21th European Symposium on Artificial Neural Networks, 
    Computational Intelligence and Machine Learning (ESANN),
    pp. 437-442, Bruges, Belgium, 24-26 Apr. 2013.
    ISBN: 978-2-87419-081-0.

  17. D. Anguita, A. Ghio, L. Oneto, X. Parra, J. L. Reyes-Ortiz, 
    Human Activity Recognition on Smartphones using a Multiclass Hardware-Friendly Support Vector Machine, 
    4th International Workshop on Ambient Assisted Living (IWAAL), 
    pp. 216-223 Vitoria-Gasteiz, Spain, 3-5 Dec. 2012.
    ISBN: 978-3-642-35394-9, DOI: 10.1007/978-3-642-35395-6_30.

  18. L. Ghelardoni, A. Ghio, D. Anguita, 
    Smart underwater wireless sensor networks, 
    Proc. of the IEEE 27th Convention of Electrical & Electronics Engineers in Israel (IEEEI),
    pp. 1-5, Eliat, Israel, 14-17 November 2012.
    ISBN: 978-1-4673-4682-5, DOI: 10.1109/EEEI.2012.6376941.

  19. D. Anguita, L. Ghelardoni, A. Ghio
    Long-Term Energy Load Forecasting Using Auto-Regressive and Approximating Support Vector Regression
    Proc. of the IEEE International Energy Conference and Exhibition (Energycon)
    pp. 842-847, Florence, Italy, 9-12 September 2012.
    ISBN: 978-1-4673-1453-4, DOI: 10.1109/EnergyCon.2012.6348269.

  20. L. Oneto, D. Anguita, A. Ghio, S. Ridella, 
    Rademacher Complexity and Structural Risk Minimization: an Application to Human Gene Expression Datasets, 
    22nd Int. Conf. on Artificial Neural Networks (ICANN), 
    pp. 491-498, Lausanne, Switzerland, 11-14 Sept. 2012.
    ISBN: 978-3-642-33265-4, DOI: 10.1007/978-3-642-33266-1_61.

  21. D. Anguita, L. Ghelardoni, A. Ghio, L. Oneto, S. Ridella, 
    The ‘K’ in K-fold Cross Validation, 
    20th European Symposium on Artificial Neural Networks, 
    Computational Intelligence and Machine Learning (ESANN), 
    pp. 441-446, Bruges, Belgium, 25-27 Apr. 2012.
    ISBN: 978-2-87419-049-0.

  22. D. Anguita, A. Ghio, L. Oneto, S. Ridella, 
    Structural Risk Minimization and Rademacher Complexity for Regression, 
    20th European Symposium on Artificial Neural Networks, 
    Computational Intelligence and Machine Learning (ESANN), 
    pp. 55-60, Bruges, Belgium, 25-27 Apr. 2012.
    ISBN: 978-2-87419-049-0.

  23. D. Anguita, A. Ghio, L. Oneto, S. Ridella, 
    The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers, 
    Advances in Neural Information Processing Systems (NIPS) 24, 
    pp. 585-593, Granada, Spain, 12-15 Dec. 2011.
    ISBN: 978-1-6183-9599-3.

  24. K. Zόr, M. Vergani, A. Heiskanen, E. Landini, M. Carminati, V. Coman, I. Vedarethinam, P. Skafte-Pedersen, M. Skolimowski, A. Martinez Serrano, M. Kokaia, T. Ramos Moreno, A. Ghio, W.E. Svendsen, M. Dimaki, Z. Keresztes, M. Adamovski, U. Wollenberger, D. Sabourin, G. Ferrari, R. Raiteri, M. Sampietro, M. Dufva, J. Emnéus, 
    Real-Time Monitoring of Cellular Dynamics Using a Microfluidic Cell Culture System with Integrated Electrode Array and Potentiostat, 
    Proc. of the International Conference on Miniaturized Systems for Chemistry and Life Sciences, 
    pp. 1532-1535, Seattle, USA, 2-6 Oct. 2011.
    ISBN: 9781618395955.

  25. D. Anguita, A. Ghio, L. Oneto, S. Ridella, 
    In-sample Model Selection for Support Vector Machines, 
    IEEE Int. Joint Conference on Neural Networks (IJCNN), 
    pp. 1154-1161, San Jose, CA, USA, 31 Jul. - 05 Aug. 2011.
    ISBN: 978-1-4244-9635-8, DOI: 10.1109/IJCNN.2011.6033354.

  26. D. Anguita, A. Ghio, L. Oneto, S. Ridella, 
    Selecting the Hypothesis Space for Improving the Generalization Ability of Support Vector Machines, 
    IEEE Int. Joint Conference on Neural Networks (IJCNN), 
    pp. 1169-1176, San Jose, CA, USA, 31 Jul. - 05 Aug. 2011.
    ISBN: 978-1-4244-9635-8, DOI: 10.1109/IJCNN.2011.6033356.

  27. D. Anguita, A. Ghio, L. Oneto, S. Ridella, 
    Maximal Discrepancy vs. Rademacher Complexity for Error Estimation, 
    19th European Symposium on Artificial Neural Networks, 
    Computational Intelligence and Machine Learning (ESANN), 
    pp. 257-262, Bruges, Belgium, 27-29 Apr. 2011.
    ISBN: 978-2-87419-044-5.

  28. D. Anguita, L. Ghelardoni, A. Ghio, S. Ridella, 
    Test Error Bounds for Classifiers: A Survey of Old and New Results, 
    Proc. of IEEE Symposium on Computational Intelligence, 
    pp. 80-87, Paris, France, 11-15 Apr. 2011.
    ISBN: 978-1-4244-9981-6, DOI: 10.1109/FOCI.2011.5949469.

  29. D. Anguita, A. Ghio, N. Greco, L. Oneto, S. Ridella, 
    Model Selection for Support Vector Machines: Advantages and Disadvantages of the Machine Learning Theory, 
    IEEE International Joint Conference on Neural Networks (IJCNN), 
    pp. 1-8, Barcelona, Spain, 18-23 Jul. 2010.
    ISBN: 978-1-4244-6916-1, DOI: 10.1109/IJCNN.2010.5596450.

  30. D. Anguita, A. Ghio, S. Ridella, 
    Maximal Discrepancy for Support Vector Machines, 
    19th European Symposium on Artificial Neural Networks, 
    Computational Intelligence and Machine Learning (ESANN), 
    pp. 13-18, Bruges, Belgium, 28-30 Apr. 2010.
    ISBN: 2-930307-10-2. 

  31. D. Anguita, A. Ghio, S. Ridella, D. Sterpi, 
    K-Fold Cross Validation for Error Rate Estimate in Support Vector Machines, 
    Proc. of the DMIN International Conference on Data Mining, 
    pp. 291-297, Las Vegas, USA, 13-16 Jul. 2009.
    ISBN: 1-60132-099-X. 

  32. E. Alba, D. Anguita, A. Ghio, S. Ridella, 
    Using Variable Neighborhood Search to Improve the Support Vector Machine Performance in Embedded Automotive Applications, 
    Proc. of IEEE World Congress on Computational Intelligence 2008, 
    pp. 984-988, Hong Kong, 1-8 Jun. 2008.
    ISBN: 978-1-4244-1821-3, DOI: 10.1109/IJCNN.2008.4633918. 

  33. D. Anguita, D. Brizzolara, A. Ghio, G. Parodi, 
    Smart Plankton: a Nature Inspired Underwater Wireless Sensor Network, 
    Proc. of IEEE Int. Conference on Natural Computing 2008, 
    pp. 701-705, Jinan, China, 18-20 Oct. 2008.
    ISBN: 978-0-7695-3304-9, DOI: 10.1109/ICNC.2008.634. 

  34. D. Anguita, D. Brizzolara, A. Ghio, G. Parodi, 
    Smart Plankton: a new generation of underwater wireless sensor network, 
    Proc. of Artificial Life XI, 
    pp. 745, Winchester, UK, 5-8 Aug. 2008.
    ISBN: 978-0-262-28719-7. 

  35. D. Anguita, A. Ghio, S. Pischiutta, S. Ridella, 
    A Hardware-friendly Support Vector Machine for Embedded Automotive Applications, 
    Proc. of IEEE Int. Joint Conference on Neural Networks 2007 (IJCNN), 
    pp. 1360-1364, Orlando, USA, 12-17 Aug. 2007.
    ISBN: 978-1-4244-1380-5, DOI: 10.1109/IJCNN.2007.4371156. 

  36. D. Anguita, A. Ghio, S. Pischiutta, 
    A Learning Machine for Resource-Limited Adaptive Hardware, 
    Proc. of NASA/ESA Int. Conference on Adaptive Hardware Systems 2007, 
    pp. 571-576, Edinburgh, UK, 5-8 Aug. 2007.
    ISBN: 978-0-7695-2866-3, DOI: 10.1109/AHS.2007.6. 

  37. A. Ghio, 
    An Embedded Pedestrian Classifier for Automotive Applications, 
    NiSIS Symposium, 
    St. Julians, Malta, 26-27 Nov. 2007.

  38. A. Ghio, S. Pischiutta, 
    A Support Vector Machine Based Pedestrian Recognition System on Resource–Limited Hardware Architectures, 
    Proc. of IEEE Ph.D. Research in Microelectronics and Electronics Conference, 2007. PRIME 2007, 
    pp. 161-163, Bordeaux, France, 2-5 Jul. 2007.
    ISBN: 978-1-4244-1001-9, DOI: 10.1109/RME.2007.4401836. 

International Workshops
  1. L. Oneto, A. Ghio, D. Anguita, S. Ridella
    Learning With Few Bits on Small-Scale Devices,  
    Workshop on Resource-Efficient Machine Learning of the Neural Information Processing Systems (NIPS),
    Lake Tahoe, Nevada, United States, 5-10 Dec. 2013.

  2. D. Anguita, A. Ghio, L. Oneto,
    A Learning Machine for Embedded Systems,
    Applications in Electronics Pervading Industry, Environment & Society,
    Rome, Italy, 7-8 Mar. 2013.

  3. D. Anguita, A. Ghio, L. Oneto, X. Parra, J. L. Reyes-Ortiz, 
    Human Activity Recognition on Smartphones for Mobile Context Awareness,  
    Workshop on Machine Learning Approaches to Mobile Context Awareness of the Neural Information Processing Systems (NIPS),
    Lake Tahoe, Nevada, United States, 3-8 Dec. 2012.

  4. D. Anguita, A. Ghio, L. Oneto, S. Ridella, 
    A Tool for Training Effective Classifiers in the Small Sample Setting, 
    Virtual Physiological Human (VPH), 
    London, UK, 18-20 Sep. 2012.

  5. D. Anguita, A. Ghio, L. Oneto, Jorge Luis Reyes-Ortiz,
    Activity Recognition Using Smartphone Inertial Sensors,
    Applications in Electronics Pervading Industry, Environment & Society,
    Rome, Italy, 11-12 Jun. 2012.

  6. D.Anguita, L.Ghelardoni, A.Ghio,
    Smart Underwater Wireless Sensor Networks,
    Applications in Electronics Pervading Industry, Environment & Society,
    Rome, Italy, 11-12 Jun. 2012.

  7. D.Anguita, L.Ghelardoni, A.Ghio,
    Auto-regressive and Approximating Support Vector Regression for Long-Term Load Forecasting,
    Applications in Electronics Pervading Industry, Environment & Society,
    Rome, Italy, 11-12 Jun. 2012.

National book chapters
  1. D. Anguita, A. Ghio
    Il Data Mining: tecniche e utilizzo,  
    In G. Bottaro, “Le 5 W della Business Intelligence”,
    Red@zione, 2009.

National conferences
  1. D. Anguita, L. Ghelardoni, A. Ghio,
    Smart Underwater Wireless Sensor Networks,
    Riunione Annuale del Gruppo Italiano di Elettronica (GIE2012),
    Marina di Carrara, 2012.

  2. D. Anguita, A. Ghio, L. Oneto, J.L. Reyes-Ortiz,
    ARApp: Smartphone Application for Activity Recognition using Embedded Inertial Sensors,
    Riunione Annuale del Gruppo Italiano di Elettronica (GIE2012),
    Marina di Carrara, 2012.

  3. D. Anguita, D. Brizzolara, L. Ghelardoni, A. Ghio, G. Parodi,
    Systems and circuits for underwater optical wireless communication,
    Riunione Annuale del Gruppo Italiano di Elettronica (GE2010),
    Frascati, 2010.

  4. D. Anguita, D. Brizzolara, A. Ghio, G. Parodi,
    Optical Communication for Underwater Wireless Sensor Networks,
    Riunione Annuale del Gruppo Italiano di Elettronica (GE2009),
    Trento, 2009.

  5. L. Benini, M. Magno, M. Oliveri, F. Menichelli, A. Boni, A. Kerhet, D. Anguita, A. Ghio,
    A Low-Power Configurable Wireless Video Sensor Node for Distributed Vision Applications,
    Riunione Annuale del Gruppo Italiano di Elettronica (GE2007),
    Lerici, 2007.





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© Alessandro Ghio, 2015