Transputer-based architectures for associative image classification. - Davide Anguita; Giancarlo Parodi; Domenico Ponta; Rodolfo Zunino (SPDP, 1991)

An efficient implementation of BP on RISC-based workstations. - Davide Anguita; Giancarlo Parodi; Rodolfo Zunino (Neurocomputing, 1994)

Associative structures for vision. - Davide Anguita; Giancarlo Parodi; Rodolfo Zunino (Multidimens. Syst. Signal Process., 1994)

Learning in large neural networks. - Davide Anguita; Filippo Passaggio; Rodolfo Zunino (HPCN Europe, 1995)

Object Oriented Design of a Simulator for Large BP Neural Networks. - Jean-Marc Adamo; Davide Anguita (IWANN, 1995)

A heterogeneous and reconfigurable machine-vision system. - Davide Anguita; Vito Di Gesù; Gaetano Gerardi; Biagio Lenzitti; Domenico Tegolo (Mach. Vis. Appl., 1995)

Neural structures for visual motion tracking. - Davide Anguita; Giancarlo Parodi; Rodolfo Zunino (Mach. Vis. Appl., 1995)

Limiting the effects of weight errors in feedforward networks using interval arithmetic. - Davide Anguita; Sandro Ridella; Stefano Rovetta; Rodolfo Zunino (ICNN, 1996)

Mixing floating- and fixed-point formats for neural network learning on neuroprocessors. - Davide Anguita; Benedict A. Gomes (Microprocess. Microprogramming, 1996)

RAIN: Redundant Array of Inexpensive workstations for Neurocomputing. - Davide Anguita; Marco Chirico; Anna Marina Scapolla; Giancarlo Parodi (Euro-Par, 1997)

High Performance Neurocomputing: Industrial and Medical Applications of the RAIN System. - Davide Anguita; Andrea Boni; Marco Chirico; Fabrizio Giudici; Anna Marina Scapolla; Giancarlo Parodi (HPCN Europe, 1998)

Support Vector Machines: A Comparison of Some Kernel Functions. - Davide Anguita; Andrea Boni; Sandro Ridella (IIA/SOCO, 1999)

A VLSI friendly algorithm for support vector machines. - Davide Anguita; Andrea Boni; Sandro Ridella (IJCNN, 1999)

Worst case analysis of weight inaccuracy effects in multilayer perceptrons. - Davide Anguita; Sandro Ridella; Stefano Rovetta (IEEE Trans. Neural Networks, 1999)

Fast Training of Support Vector Machines for Regression. - Davide Anguita; Andrea Boni; Stefano Pace (IJCNN (5), 2000)

Digital VLSI Algorithms and Architectures for Support Vector Machines. - Davide Anguita; Andrea Boni; Sandro Ridella (Int. J. Neural Syst., 2000)

A case study of a distributed high-performance computing system for neurocomputing. - Davide Anguita; Andrea Boni; Giancarlo Parodi (J. Syst. Archit., 2000)

Evaluating the Generalization Ability of Support Vector Machines through the Bootstrap. - Davide Anguita; Andrea Boni; Sandro Ridella (Neural Process. Lett., 2000)

Perspectives on dedicated hardware implementations. - Davide Anguita; Maurizio Valle (ESANN, 2001)

MDL Based Model Selection for Relevance Vector Regression. - Davide Anguita; Matteo Gagliolo (ICANN, 2002)

Automatic Hyperparameter Tuning for Support Vector Machines. - Davide Anguita; Sandro Ridella; Fabio Rivieccio; Rodolfo Zunino (ICANN, 2002)

SVM performance assessment for the control of injection moulding processes and plasticating extrusion. - Davide Anguita; Andrea Boni; L. Tagliafico (Int. J. Syst. Sci., 2002)

Improved neural network for SVM learning. - Davide Anguita; Andrea Boni (IEEE Trans. Neural Networks, 2002)

SVM learning with fixed-point math. - Davide Anguita; Andrea Boni; Sandro Ridella (IJCNN, 2003)

Training support vector machines: a quantum-computing perspective. - Davide Anguita; Sandro Ridella; Fabio Rivieccio; Rodolfo Zunino (IJCNN, 2003)

Neural network learning for analog VLSI implementations of support vector machines: a survey. - Davide Anguita; Andrea Boni (Neurocomputing, 2003)

Hyperparameter design criteria for support vector classifiers. - Davide Anguita; Sandro Ridella; Fabio Rivieccio; Rodolfo Zunino (Neurocomputing, 2003)

Quantum optimization for training support vector machines. - Davide Anguita; Sandro Ridella; Fabio Rivieccio; Rodolfo Zunino (Neural Networks, 2003)

Digital Least Squares Support Vector Machines. - Davide Anguita; Andrea Boni (Neural Process. Lett., 2003)

A digital architecture for support vector machines: theory, algorithm, and FPGA implementation. - Davide Anguita; Andrea Boni; Sandro Ridella (IEEE Trans. Neural Networks, 2003)

Mapping LSSVM on digital hardware. - Davide Anguita; Andrea Boni; Alessandro Zorat (IJCNN, 2004)

Unsupervised clustering and the capacity of support vector machines. - Davide Anguita; Sandro Ridella; Fabio Rivieccio; Rodolfo Zunino (IJCNN, 2004)

A new method for multiclass support vector machines. - Davide Anguita; Sandro Ridella; Dario Sterpi (IJCNN, 2004)

An Algorithm for Reducing the Number of Support Vectors. - Davide Anguita; Sandro Ridella; Fabio Rivieccio (WIRN, 2004)

Special issue on hardware implementations of soft computing techniques. - Davide Anguita; Iluminada Baturone; Julian Francis Miller (Appl. Soft Comput., 2004)

Data Mining Tools: From Web to Grid Architectures. - Davide Anguita; Arianna Poggi; Fabio Rivieccio; Anna Marina Scapolla (EGC, 2005)

The effect of quantization on support vector machines with Gaussian kernel. - Davide Anguita; Giovanni Bozza (IJCNN, 2005)

K-fold generalization capability assessment for support vector classifiers. - Davide Anguita; Sandro Ridella; Fabio Rivieccio (IJCNN, 2005)

Testing the Augmented Binary Multiclass SVM on Microarray Data. - Davide Anguita; Sandro Ridella; Dario Sterpi (IJCNN, 2006)

Nature Inspiration for Support Vector Machines. - Davide Anguita; Dario Sterpi (KES (2), 2006)

Feed-Forward Support Vector Machine Without Multipliers. - Davide Anguita; Stefano Pischiutta; Sandro Ridella; Dario Sterpi (IEEE Trans. Neural Networks, 2006)

A learning machine for resource-limited adaptive hardware. - Davide Anguita; Alessandro Ghio; Stefano Pischiutta (AHS, 2007)

Interval discriminant analysis using support vector machines. - Cecilio Angulo; Davide Anguita; Luis González Abril (ESANN, 2007)

A Hardware-friendly Support Vector Machine for Embedded Automotive Applications. - Davide Anguita; Alessandro Ghio; Stefano Pischiutta; Sandro Ridella (IJCNN, 2007)

Smart plankton - a new generation of underwater wireless sensor network. - Davide Anguita; Davide Brizzolara; Alessandro Ghio; Giancarlo Parodi (ALIFE, 2008)

Smart Plankton: a Nature Inspired Underwater Wireless Sensor Network. - Davide Anguita; Davide Brizzolara; Alessandro Ghio; Giancarlo Parodi (ICNC (7), 2008)

Using Variable Neighborhood Search to improve the Support Vector Machine performance in embedded automotive applications. - Enrique Alba 001; Davide Anguita; Alessandro Ghio; Sandro Ridella (IJCNN, 2008)

A support vector machine with integer parameters. - Davide Anguita; Alessandro Ghio; Stefano Pischiutta; Sandro Ridella (Neurocomputing, 2008)

Support vector machines for interval discriminant analysis. - Cecilio Angulo; Davide Anguita; Luis González Abril; Juan Antonio Ortega 001 (Neurocomputing, 2008)

K-Fold Cross Validation for Error Rate Estimate in Support Vector Machines. - Davide Anguita; Alessandro Ghio; Sandro Ridella; Dario Sterpi (DMIN, 2009)

Nature-inspired learning and adaptive systems. - Bogdan Gabrys; Davide Anguita (Nat. Comput., 2009)

Model selection for support vector machines: Advantages and disadvantages of the Machine Learning Theory. - Davide Anguita; Alessandro Ghio; Noemi Greco; Luca Oneto; Sandro Ridella (IJCNN, 2010)

Using unsupervised analysis to constrain generalization bounds for support vector classifiers. - Sergio Decherchi; Sandro Ridella; Rodolfo Zunino; Paolo Gastaldo; Davide Anguita (IEEE Trans. Neural Networks, 2010)

Maximal Discrepancy vs. Rademacher Complexity for error estimation. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (ESANN, 2011)

Test error bounds for classifiers: A survey of old and new results. - Davide Anguita; Luca Ghelardoni; Alessandro Ghio; Sandro Ridella (FOCI, 2011)

In-sample model selection for Support Vector Machines. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (IJCNN, 2011)

Selecting the hypothesis space for improving the generalization ability of Support Vector Machines. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (IJCNN, 2011)

The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers. - Luca Oneto; Davide Anguita; Alessandro Ghio; Sandro Ridella (NIPS, 2011)

Maximal Discrepancy for Support Vector Machines. - Davide Anguita; Alessandro Ghio; Sandro Ridella (Neurocomputing, 2011)

A FPGA Core Generator for Embedded Classification Systems. - Davide Anguita; Luca Carlino; Alessandro Ghio; Sandro Ridella (J. Circuits Syst. Comput., 2011)

The 'K' in K-fold Cross Validation. - Davide Anguita; Luca Ghelardoni; Alessandro Ghio; Luca Oneto; Sandro Ridella (ESANN, 2012)

Structural Risk Minimization and Rademacher Complexity for Regression. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (ESANN, 2012)

Nested Sequential Minimal Optimization for Support Vector Machines. - Alessandro Ghio; Davide Anguita; Luca Oneto; Sandro Ridella; Carlotta Schatten (ICANN (2), 2012)

Rademacher Complexity and Structural Risk Minimization: An Application to Human Gene Expression Datasets. - Luca Oneto; Davide Anguita; Alessandro Ghio; Sandro Ridella (ICANN (2), 2012)

Human Activity Recognition on Smartphones Using a Multiclass Hardware-Friendly Support Vector Machine. - Davide Anguita; Alessandro Ghio; Luca Oneto; Xavier Parra; Jorge Luis Reyes-Ortiz (IWAAL, 2012)

In-sample Model Selection for Trimmed Hinge Loss Support Vector Machine. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (Neural Process. Lett., 2012)

In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (IEEE Trans. Neural Networks Learn. Syst., 2012)

Human Activity Recognition Using Smartphones. - Jorge Luis Reyes-Ortiz; Davide Anguita; Alessandro Ghio; Luca Oneto; Xavier Parra (UCI Machine Learning Repository, 2012)

A Public Domain Dataset for Human Activity Recognition using Smartphones. - Davide Anguita; Alessandro Ghio; Luca Oneto; Xavier Parra; Jorge Luis Reyes-Ortiz (ESANN, 2013)

A Learning Machine with a Bit-Based Hypothesis Space. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (ESANN, 2013)

Human Activity and Motion Disorder Recognition: towards smarter Interactive Cognitive Environments. - Jorge Luis Reyes-Ortiz; Alessandro Ghio; Xavier Parra; Davide Anguita; Joan Cabestany; Andreu Català (ESANN, 2013)

Training Computationally Efficient Smartphone-Based Human Activity Recognition Models. - Davide Anguita; Alessandro Ghio; Luca Oneto; Xavier Parra; Jorge Luis Reyes-Ortiz (ICANN, 2013)

A Novel Procedure for Training L1-L2 Support Vector Machine Classifiers. - Davide Anguita; Alessandro Ghio; Luca Oneto; Jorge Luis Reyes-Ortiz; Sandro Ridella (ICANN, 2013)

Some results about the Vapnik-Chervonenkis entropy and the rademacher complexity. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (IJCNN, 2013)

A support vector machine classifier from a bit-constrained, sparse and localized hypothesis space. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (IJCNN, 2013)

A Survey of old and New Results for the Test Error Estimation of a Classifier. - Davide Anguita; Luca Ghelardoni; Alessandro Ghio; Sandro Ridella (J. Artif. Intell. Soft Comput. Res., 2013)

Energy Efficient Smartphone-Based Activity Recognition using Fixed-Point Arithmetic. - Davide Anguita; Alessandro Ghio; Luca Oneto; Xavier Parra; Jorge Luis Reyes-Ortiz (J. Univers. Comput. Sci., 2013)

An improved analysis of the Rademacher data-dependent bound using its self bounding property. - Luca Oneto; Alessandro Ghio; Davide Anguita; Sandro Ridella (Neural Networks, 2013)

Energy Load Forecasting Using Empirical Mode Decomposition and Support Vector Regression. - Luca Ghelardoni; Alessandro Ghio; Davide Anguita (IEEE Trans. Smart Grid, 2013)

A Learning Analytics Methodology to Profile Students Behavior and Explore Interactions with a Digital Electronics Simulator. - Mehrnoosh Vahdat; Luca Oneto; Alessandro Ghio; Giuliano Donzellini; Davide Anguita; Mathias Funk; Matthias Rauterberg (EC-TEL, 2014)

Learning with few bits on small-scale devices: From regularization to energy efficiency. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (ESANN, 2014)

Human Activity Recognition on Smartphones with Awareness of Basic Activities and Postural Transitions. - Jorge Luis Reyes-Ortiz; Luca Oneto; Alessandro Ghio; Albert Samà; Davide Anguita; Xavier Parra (ICANN, 2014)

Out-of-Sample Error Estimation: The Blessing of High Dimensionality. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Jorge Luis Reyes-Ortiz; Davide Anguita (ICDM Workshops, 2014)

Smartphone battery saving by bit-based hypothesis spaces and local Rademacher Complexities. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (IJCNN, 2014)

Unlabeled patterns to tighten Rademacher complexity error bounds for kernel classifiers. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (Pattern Recognit. Lett., 2014)

A Deep Connection Between the Vapnik-Chervonenkis Entropy and the Rademacher Complexity. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (IEEE Trans. Neural Networks Learn. Syst., 2014)

Condition Based Maintenance of Naval Propulsion Plants. - Andrea Coraddu; Luca Oneto; Alessandro Ghio; Stefano Savio; Davide Anguita; Massimo Figari (UCI Machine Learning Repository, 2014)

Performance assessment and uncertainty quantification of predictive models for smart manufacturing systems. - Luca Oneto; Ilenia Orlandi; Davide Anguita (IEEE BigData, 2015)

A Learning Analytics Approach to Correlate the Academic Achievements of Students with Interaction Data from an Educational Simulator. - Mehrnoosh Vahdat; Luca Oneto; Davide Anguita; Mathias Funk; Matthias Rauterberg (EC-TEL, 2015)

Model Selection for Big Data: Algorithmic Stability and Bag of Little Bootstraps on GPUs. - Luca Oneto; Bernardo Pilarz; Alessandro Ghio; Davide Anguita (ESANN, 2015)

Advances in learning analytics and educational data mining. - Mehrnoosh Vahdat; Alessandro Ghio; Luca Oneto; Davide Anguita; Mathias Funk; Matthias Rauterberg (ESANN, 2015)

Human Algorithmic Stability and Human Rademacher Complexity. - Mehrnoosh Vahdat; Luca Oneto; Alessandro Ghio; Davide Anguita; Mathias Funk; Matthias Rauterberg (ESANN, 2015)

Shrinkage learning to improve SVM with hints. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Davide Anguita (IJCNN, 2015)

Support vector machines and strictly positive definite kernel: The regularization hyperparameter is more important than the kernel hyperparameters. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Davide Anguita (IJCNN, 2015)

Fast convergence of extended Rademacher Complexity bounds. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Davide Anguita (IJCNN, 2015)

Condition Based Maintenance in Railway Transportation Systems Based on Big Data Streaming Analysis. - Emanuele Fumeo; Luca Oneto; Davide Anguita (INNS Conference on Big Data, 2015)

Big Data Analytics in the Cloud: Spark on Hadoop vs MPI/OpenMP on Beowulf. - Jorge Luis Reyes-Ortiz; Luca Oneto; Davide Anguita (INNS Conference on Big Data, 2015)

Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Davide Anguita (Neurocomputing, 2015)

Local Rademacher Complexity: Sharper risk bounds with and without unlabeled samples. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Davide Anguita (Neural Networks, 2015)

Fully Empirical and Data-Dependent Stability-Based Bounds. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Davide Anguita (IEEE Trans. Cybern., 2015)

Smartphone-Based Recognition of Human Activities and Postural Transitions. - Jorge Luis Reyes-Ortiz; Davide Anguita; Luca Oneto; Xavier Parra (UCI Machine Learning Repository, 2015)

Educational Process Mining (EPM): A Learning Analytics Data Set. - Mehrnoosh Vahdat; Luca Oneto; Davide Anguita; Mathias Funk; Matthias Rauterberg (UCI Machine Learning Repository, 2015)

Advanced Analytics for Train Delay Prediction Systems by Including Exogenous Weather Data. - Luca Oneto; Emanuele Fumeo; Giorgio Clerico; Renzo Canepa; Federico Papa; Carlo Dambra; Nadia Mazzino; Davide Anguita (DSAA, 2016)

Learning Analytics for a Puzzle Game to Discover the Puzzle-Solving Tactics of Players. - Mehrnoosh Vahdat; Maira B. Carvalho; Mathias Funk; Matthias Rauterberg; Jun Hu 001; Davide Anguita (EC-TEL, 2016)

Advances in Learning with Kernels: Theory and Practice in a World of growing Constraints. - Luca Oneto; Nicolò Navarin; Michele Donini; Fabio Aiolli; Davide Anguita (ESANN, 2016)

Measuring the Expressivity of Graph Kernels through the Rademacher Complexity. - Luca Oneto; Nicolò Navarin; Michele Donini; Alessandro Sperduti; Fabio Aiolli; Davide Anguita (ESANN, 2016)

Tuning the Distribution Dependent Prior in the PAC-Bayes Framework based on Empirical Data. - Luca Oneto; Sandro Ridella; Davide Anguita (ESANN, 2016)

Random Forests Model Selection. - Ilenia Orlandi; Luca Oneto; Davide Anguita (ESANN, 2016)

Delay Prediction System for Large-Scale Railway Networks Based on Big Data Analytics. - Luca Oneto; Emanuele Fumeo; Giorgio Clerico; Renzo Canepa; Federico Papa; Carlo Dambra; Nadia Mazzino; Davide Anguita (INNS Conference on Big Data, 2016)

Vessel monitoring and design in industry 4.0: A data driven perspective. - Luca Oneto; Davide Anguita; Andrea Coraddu; Toine Cleophas; Katerina Xepapa (RTSI, 2016)

Statistical Learning Theory and ELM for Big Social Data Analysis. - Luca Oneto; Federica Bisio; Erik Cambria; Davide Anguita (IEEE Comput. Intell. Mag., 2016)

Transition-Aware Human Activity Recognition Using Smartphones. - Jorge Luis Reyes-Ortiz; Luca Oneto; Albert Samà; Xavier Parra; Davide Anguita (Neurocomputing, 2016)

Can machine learning explain human learning? - Mehrnoosh Vahdat; Luca Oneto; Davide Anguita; Mathias Funk; Matthias Rauterberg (Neurocomputing, 2016)

Tikhonov, Ivanov and Morozov regularization for support vector machine learning. - Luca Oneto; Sandro Ridella; Davide Anguita (Mach. Learn., 2016)

A local Vapnik-Chervonenkis complexity. - Luca Oneto; Davide Anguita; Sandro Ridella (Neural Networks, 2016)

Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Davide Anguita (Neural Process. Lett., 2016)

PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis. - Luca Oneto; Davide Anguita; Sandro Ridella (Pattern Recognit. Lett., 2016)

Learning Hardware-Friendly Classifiers Through Algorithmic Stability. - Luca Oneto; Sandro Ridella; Davide Anguita (ACM Trans. Embed. Comput. Syst., 2016)

Learning Hardware Friendly Classifiers Through Algorithmic Risk Minimization. - Luca Oneto; Davide Anguita (Advances in Neural Networks, 2016)

Crack random forest for arbitrary large datasets. - Alessandro Lulli; Luca Oneto; Davide Anguita (IEEE BigData, 2017)

Generalization Performances of Randomized Classifiers and Algorithms built on Data Dependent Distributions. - Luca Oneto; Sandro Ridella; Davide Anguita (ESANN, 2017)

Dropout Prediction at University of Genoa: a Privacy Preserving Data Driven Approach. - Luca Oneto; Anna Siri; Gianvittorio Luria; Davide Anguita (ESANN, 2017)

ReForeSt: Random Forests in Apache Spark. - Alessandro Lulli; Luca Oneto; Davide Anguita (ICANN (2), 2017)

Marine Safety and Data Analytics: Vessel Crash Stop Maneuvering Performance Prediction. - Luca Oneto; Andrea Coraddu; Paolo Sanetti; Olena Karpenko; Francesca Cipollini; Toine Cleophas; Davide Anguita (ICANN (2), 2017)

Deep graph node kernels: A convex approach. - Luca Oneto; Nicolò Navarin; Alessandro Sperduti; Davide Anguita (IJCNN, 2017)

Semi-supervised Learning for Affective Common-Sense Reasoning. - Luca Oneto; Federica Bisio; Erik Cambria; Davide Anguita (Cogn. Comput., 2017)

SLT-Based ELM for Big Social Data Analysis. - Luca Oneto; Federica Bisio; Erik Cambria; Davide Anguita (Cogn. Comput., 2017)

Measuring the expressivity of graph kernels through Statistical Learning Theory. - Luca Oneto; Nicolò Navarin; Michele Donini; Alessandro Sperduti; Fabio Aiolli; Davide Anguita (Neurocomputing, 2017)

Differential privacy and generalization: Sharper bounds with applications. - Luca Oneto; Sandro Ridella; Davide Anguita (Pattern Recognit. Lett., 2017)

Support Vector Motion Clustering. - Isah Abdullahi Lawal; Fabio Poiesi; Davide Anguita; Andrea Cavallaro (IEEE Trans. Circuits Syst. Video Technol., 2017)

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; Federico Papa; Carlo Dambra; Nadia Mazzino; Davide Anguita (IEEE Trans. Syst. Man Cybern. Syst., 2017)

Large-Scale Railway Networks Train Movements: A Dynamic, Interpretable, and Robust Hybrid Data Analytics System. - Alessandro Lulli; Luca Oneto; Renzo Canepa; Simone Petralli; Davide Anguita (DSAA, 2018)

Emerging trends in machine learning: beyond conventional methods and data. - Luca Oneto; Nicolò Navarin; Michele Donini; Davide Anguita (ESANN, 2018)

Unintrusive Monitoring of Induction Motors Bearings via Deep Learning on Stator Currents. - Francesca Cipollini; Luca Oneto; Andrea Coraddu; Stefano Savio; Davide Anguita (INNS Conference on Big Data, 2018)

Train Delay Prediction Systems: A Big Data Analytics Perspective. - Luca Oneto; Emanuele Fumeo; Giorgio Clerico; Renzo Canepa; Federico Papa; Carlo Dambra; Nadia Mazzino; Davide Anguita (Big Data Res., 2018)

Randomized learning: Generalization performance of old and new theoretically grounded algorithms. - Luca Oneto; Francesca Cipollini; Sandro Ridella; Davide Anguita (Neurocomputing, 2018)

Multilayer Graph Node Kernels: Stacking While Maintaining Convexity. - Luca Oneto; Nicolò Navarin; Alessandro Sperduti; Davide Anguita (Neural Process. Lett., 2018)

Condition-based maintenance of naval propulsion systems: Data analysis with minimal feedback. - Francesca Cipollini; Luca Oneto; Andrea Coraddu; Alan John Murphy; Davide Anguita (Reliab. Eng. Syst. Saf., 2018)

Data-Driven Photovoltaic Power Production Nowcasting and Forecasting for Polygeneration Microgrids. - Luca Oneto; Federica Laureri; Michela Robba; Federico Delfino; Davide Anguita (IEEE Syst. J., 2018)

Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels. - Luca Oneto; Nicolò Navarin; Michele Donini; Sandro Ridella; Alessandro Sperduti; Fabio Aiolli; Davide Anguita (IEEE Trans. Neural Networks Learn. Syst., 2018)

Cavitation Noise Spectra Prediction with Hybrid Models. - Francesca Cipollini; Fabiana Miglianti; Luca Oneto; Giorgio Tani; Michele Viviani; Davide Anguita (INNSBDDL, 2019)

Train Overtaking Prediction in Railway Networks: A Big Data Perspective. - Luca Oneto; Irene Buselli; Alessandro Lulli; Renzo Canepa; Simone Petralli; Davide Anguita (INNSBDDL, 2019)

Restoration Time Prediction in Large Scale Railway Networks: Big Data and Interpretability. - Luca Oneto; Irene Buselli; Paolo Sanetti; Renzo Canepa; Simone Petralli; Davide Anguita (INNSBDDL, 2019)

Introduction. - Luca Oneto; Nicolò Navarin; Alessandro Sperduti; Davide Anguita (INNSBDDL (Tutorials), 2019)

Visual Analytics for Supporting Conflict Resolution in Large Railway Networks. - Udo Schlegel; Wolfgang Jentner; Juri Buchmüller; Eren Cakmak; Giuliano Castiglia; Renzo Canepa; Simone Petralli; Luca Oneto; Daniel A. Keim; Davide Anguita (INNSBDDL, 2019)

Improving Railway Maintenance Actions with Big Data and Distributed Ledger Technologies. - Roberto Spigolon; Luca Oneto; Dimitar Anastasovski; Nadia Fabrizio; Marie Swiatek; Renzo Canepa; Davide Anguita (INNSBDDL, 2019)

Prescriptive Maintenance of Railway Infrastructure: From Data Analytics to Decision Support. - Alice Consilvio; Paolo Sanetti; Davide Anguita; Carlo Crovetto; Carlo Dambra; Luca Oneto; Federico Papa; Nicola Sacco (MT-ITS, 2019)

Mining Big Data with Random Forests. - Alessandro Lulli; Luca Oneto; Davide Anguita (Cogn. Comput., 2019)

Local Rademacher Complexity Machine. - Luca Oneto; Sandro Ridella; Davide Anguita (Neurocomputing, 2019)

Improving the Union Bound: a Distribution Dependent Approach. - Luca Oneto; Sandro Ridella; Davide Anguita (ESANN, 2020)

Bridging Cognitive Models and Recommender Systems. - Cecilio Angulo; Zoe Falomir; Davide Anguita; Núria Agell; Erik Cambria (Cogn. Comput., 2020)

Understanding Violin Players' Skill Level Based on Motion Capture: a Data-Driven Perspective. - Vincenzo Stefano D'Amato; Erica Volta; Luca Oneto; Gualtiero Volpe; Antonio Camurri; Davide Anguita (Cogn. Comput., 2020)

A dynamic, interpretable, and robust hybrid data analytics system for train movements in large-scale railway networks. - Luca Oneto; Irene Buselli; Alessandro Lulli; Renzo Canepa; Simone Petralli; Davide Anguita (Int. J. Data Sci. Anal., 2020)

Spectral Analysis of Electricity Demand Using Hilbert-Huang Transform. - Joaquín Luque; Davide Anguita; Francisco Pérez; Robert Denda (Sensors, 2020)

Keep it Simple: Handcrafting Feature and Tuning Random Forests and XGBoost to face the Affective Movement Recognition Challenge 2021. - Vincenzo Stefano D'Amato; Luca Oneto; Antonio Camurri; Davide Anguita (ACII (Workshops and Demos), 2021)

In-Station Train Movements Prediction: from Shallow to Deep Multi Scale Models. - Gianluca Boleto; Luca Oneto; Matteo Cardellini; Marco Maratea; Mauro Vallati; Renzo Canepa; Davide Anguita (ESANN, 2021)

The Benefits of Adversarial Defence in Generalisation. - Luca Oneto; Sandro Ridella; Davide Anguita (ESANN, 2021)

Learn and Visually Explain Deep Fair Models: an Application to Face Recognition. - Danilo Franco; Luca Oneto; Nicolò Navarin; Davide Anguita (IJCNN, 2021)

Accuracy and Intrusiveness in Data-Driven Violin Players Skill Levels Prediction: MOCAP Against MYO Against KINECT. - Vincenzo Stefano D'Amato; Erica Volta; Luca Oneto; Gualtiero Volpe; Antonio Camurri; Davide Anguita (IWANN (2), 2021)

Toward Learning Trustworthily from Data Combining Privacy, Fairness, and Explainability: An Application to Face Recognition. - Danilo Franco; Luca Oneto; Nicolò Navarin; Davide Anguita (Entropy, 2021)

Simple Non Regressive Informed Machine Learning Model for Predictive Maintenance of Railway Critical Assets. - Luca Oneto; Simone Minisi; Andrea Garrone; Renzo Canepa; Carlo Dambra; Davide Anguita (ESANN, 2022)

Do We Really Need a New Theory to Understand the Double-Descent? - Luca Oneto; Sandro Ridella; Davide Anguita (ESANN, 2022)

The Importance of Multiple Temporal Scales in Motion Recognition: when Shallow Model can Support Deep Multi Scale Models. - Vincenzo Stefano D'Amato; Luca Oneto; Antonio Camurri; Davide Anguita (IJCNN, 2022)

The Importance of Multiple Temporal Scales in Motion Recognition: from Shallow to Deep Multi Scale Models. - Vincenzo Stefano D'Amato; Luca Oneto; Antonio Camurri; Davide Anguita; Zinat Zarandi; Luciano Fadiga; Alessandro D'Ausilio; Thierry Pozzo (IJCNN, 2022)

Simple Non Regressive Informed Machine Learning Model for Prescriptive Maintenance of Track Circuits in a Subway Environment. - Andrea Garrone; Simone Minisi; Luca Oneto; Carlo Dambra; Marco Borinato; Paolo Sanetti; Giulia Vignola; Federico Papa; Nadia Mazzino; Davide Anguita (SYSINT, 2022)

Deep fair models for complex data: Graphs labeling and explainable face recognition. - Danilo Franco; Nicolò Navarin; Michele Donini; Davide Anguita; Luca Oneto (Neurocomputing, 2022)

The benefits of adversarial defense in generalization. - Luca Oneto; Sandro Ridella; Davide Anguita (Neurocomputing, 2022)

Optimizing Fuel Consumption in Thrust Allocation for Marine Dynamic Positioning Systems. - Miltiadis Kalikatzarakis; Andrea Coraddu; Luca Oneto; Davide Anguita (IEEE Trans Autom. Sci. Eng., 2022)

Introduzione al Progetto di Sistemi Digitali, 2a Edition - Giuliano Donzellini; Luca Oneto; Domenico Ponta; Davide Anguita (Springer, 2023)

Mitigating Robustness Bias: Theoretical Results and Empirical Evidences. - Danilo Franco; Luca Oneto; Davide Anguita (ESANN, 2023)

Towards Randomized Algorithms and Models that We Can Trust: a Theoretical Perspective. - Luca Oneto; Sandro Ridella; Davide Anguita (ESANN, 2023)

Fair Empirical Risk Minimization Revised. - Danilo Franco; Luca Oneto; Davide Anguita (IWANN (1), 2023)

Physics Informed Data Driven Techniques for Power Flow Analysis. - Guido Parodi; Luca Oneto; Giulio Ferro; Stefano Zampini; Michela Robba; Davide Anguita; Andrea Coraddu (SSCI, 2023)

Do we really need a new theory to understand over-parameterization? - Luca Oneto; Sandro Ridella; Davide Anguita (Neurocomputing, 2023)

New Advances in Artificial Neural Networks and Machine Learning Techniques. - Olga Valenzuela; Andreu Català; Davide Anguita; Ignacio Rojas (Neural Process. Lett., 2023)

Informed Machine Learning for Complex Data. - Luca Oneto; Nicolò Navarin; Alessio Micheli; Luca Pasa; Claudio Gallicchio; Davide Bacciu; Davide Anguita (ESANN, 2024)

Mitigating Unfair Regression in Machine Learning Model Updates. - Irene Buselli; Anna Pallarès López; Eduard Martín Jiménez; Davide Anguita; Fabio Roli; Luca Oneto (ICMLA, 2024)

Toward Measuring and Understanding the Overvalidation Phenomena. - Fabrizio Mori; Antonio Emanuele Cinà; Fabio Roli; Davide Anguita; Luca Oneto (ICMLA, 2024)

Traffic Simulator AI-Based Surrogate for an Urban Road Network. - F. Cantatore; G. Raimondi; Luca Oneto; Andrea Coraddu; Cecilia Pasquale; Enrico Siri; Silvia Siri; Simona Sacone; Davide Anguita (ITSC, 2024)

Investigating over-parameterized randomized graph networks. - Giovanni Donghi; Luca Pasa; Luca Oneto; Claudio Gallicchio; Alessio Micheli; Davide Anguita; Alessandro Sperduti; Nicolò Navarin (Neurocomputing, 2024)

Towards algorithms and models that we can trust: A theoretical perspective. - Luca Oneto; Sandro Ridella; Davide Anguita (Neurocomputing, 2024)

Provably Efficient and Robust Conformal Prediction under a Realistic Threat Model. - Alberto Carlevaro; Luca Oneto; Davide Anguita; Fabio Roli (COPA, 2025)

Dynamical Systems Behavior Prediction: Machine Learning and Koopman Operator. - Enrico Zero; Luca Oneto; Roberto Sacile; Davide Anguita (SoSE, 2025)

Informed Machine Learning: Excess risk and generalization. - Luca Oneto; Sandro Ridella; Davide Anguita (Neurocomputing, 2025)

A review on full-, zero-, and partial-knowledge based predictive models for industrial applications. - Stefano Zampini; Guido Parodi; Luca Oneto; Andrea Coraddu; Davide Anguita (Inf. Fusion, 2025)

Training-Free Constrained Generation With Stable Diffusion Models. - Stefano Zampini; Jacob Christopher; Luca Oneto; Davide Anguita; Ferdinando Fioretto (CoRR, 2025)

Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates. - Daniele Angioni; Luca Demetrio; Maura Pintor; Luca Oneto; Davide Anguita; Battista Biggio; Fabio Roli (IEEE Trans. Pattern Anal. Mach. Intell., 2025)