Davide Anguita

Enrique Alba, Davide Anguita, Sandro Ridella, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

A heterogeneous and reconfigurable machine-vision system

Vito Di Gesù, Davide Anguita, Gaetano Gerardi, 2005, Machine Vision and Applications.

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

Davide Anguita, Luca Oneto, Sandro Ridella, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Energy Load Forecasting Using Empirical Mode Decomposition and Support Vector Regression

Davide Anguita, Alessandro Ghio, Luca Ghelardoni, 2013, IEEE Transactions on Smart Grid.

Support Vector Machines: A Comparison of Some Kernel Functions

Davide Anguita, Andrea Boni, Sandro Ridella, 1999, IIA/SOCO.

Complements in Combinational Network Design

Davide Anguita, Luca Oneto, Domenico Ponta, 2019 .

Some results about the Vapnik-Chervonenkis entropy and the rademacher complexity

Davide Anguita, Luca Oneto, Sandro Ridella, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Can machine learning explain human learning?

Davide Anguita, Luca Oneto, Matthias Rauterberg, 2016, Neurocomputing.

Combinational Network Design

Davide Anguita, Luca Oneto, Domenico Ponta, 2019 .

The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers

Davide Anguita, Luca Oneto, Sandro Ridella, 2011, NIPS.

Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates

Davide Anguita, Luca Oneto, Sandro Ridella, 2015, Neural Processing Letters.

Learning Analytics for a Puzzle Game to Discover the Puzzle-Solving Tactics of Players

Jun Hu, Davide Anguita, Matthias Rauterberg, 2016, EC-TEL.

Randomized learning: Generalization performance of old and new theoretically grounded algorithms

Davide Anguita, Luca Oneto, Sandro Ridella, 2018, Neurocomputing.

Test error bounds for classifiers: A survey of old and new results

Davide Anguita, Sandro Ridella, Alessandro Ghio, 2011, 2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI).

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

Davide Anguita, Luca Oneto, Francesco Baldi, 2017 .

Block distortion assessment for image compression through ANNs

Davide Anguita, Sandro Ridella, Ivano Barbieri, 1996, Electronic Imaging.

Deep graph node kernels: A convex approach

Alessandro Sperduti, Davide Anguita, Luca Oneto, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Testing the Augmented Binary Multiclass SVM on Microarray Data

Davide Anguita, Sandro Ridella, Dario Sterpi, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Data-Driven Photovoltaic Power Production Nowcasting and Forecasting for Polygeneration Microgrids

Federico Delfino, Michela Robba, Davide Anguita, 2018, IEEE Systems Journal.

A FPGA Core Generator for Embedded Classification Systems

Davide Anguita, Sandro Ridella, Alessandro Ghio, 2011, J. Circuits Syst. Comput..

A Learning Analytics Methodology to Profile Students Behavior and Explore Interactions with a Digital Electronics Simulator

Davide Anguita, Luca Oneto, Matthias Rauterberg, 2014, EC-TEL.

The Digital Kernel Perceptron

Davide Anguita, Andrea Boni, Sandro Ridella, 2002 .

Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency

Davide Anguita, Luca Oneto, Sandro Ridella, 2015, Neurocomputing.

Novel efficient technologies in Europe for axle bearing condition monitoring – the MAXBE project

Davide Anguita, Frederik Vermeulen, Rui Calçada, 2016 .

Limiting the effects of weight errors in feedforward networks using interval arithmetic

Davide Anguita, Sandro Ridella, Rodolfo Zunino, 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

Training Computationally Efficient Smartphone-Based Human Activity Recognition Models

Davide Anguita, Luca Oneto, Alessandro Ghio, 2013, ICANN.

Machine Learning algorithms for Data Mining

Davide Anguita, D. Anguita, 2011 .

An Innovative Technique for the Aerodynamic Design of Turbine Profiles Using Artificial Intelligence (Invited)

Davide Anguita, Fabio Rivieccio, Carlo Cravero, 2003 .

Learning Hardware-Friendly Classifiers Through Algorithmic Stability

Davide Anguita, Luca Oneto, Sandro Ridella, 2016, ACM Trans. Embed. Comput. Syst..

Generalization Performances of Randomized Classifiers and Algorithms built on Data Dependent Distributions

Davide Anguita, Luca Oneto, Sandro Ridella, 2017, ESANN.

Transition-Aware Human Activity Recognition Using Smartphones

Davide Anguita, Luca Oneto, Albert Samà, 2016, Neurocomputing.

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

Davide Anguita, Luca Oneto, Jorge Luis Reyes-Ortiz, 2015, INNS Conference on Big Data.

Learning with few bits on small-scale devices: From regularization to energy efficiency

Davide Anguita, Luca Oneto, Sandro Ridella, 2014, ESANN.

A case study of a distributed high-performance computing system for neurocomputing

Davide Anguita, Andrea Boni, Giancarlo Parodi, 2000, J. Syst. Archit..

A Comparative Study of NN and SVM-Based Electromagnetic Inverse Scattering Approaches to On-Line Detection of Buried Objects

Davide Anguita, Andrea Boni, Salvatore Caorsi, 2003 .

Quantum optimization for training support vector machines

Davide Anguita, Sandro Ridella, Rodolfo Zunino, 2003, Neural Networks.

Using Unsupervised Analysis to Constrain Generalization Bounds for Support Vector Classifiers

Davide Anguita, Sandro Ridella, Paolo Gastaldo, 2010, IEEE Transactions on Neural Networks.

Support vector machines for interval discriminant analysis

Davide Anguita, Luis González Abril, Juan Antonio Ortega, 2008, Neurocomputing.

Fast convergence of extended Rademacher Complexity bounds

Davide Anguita, Luca Oneto, Sandro Ridella, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Condition-based maintenance of naval propulsion systems: Data analysis with minimal feedback

Davide Anguita, Luca Oneto, Andrea Coraddu, 2018, Reliab. Eng. Syst. Saf..

A support vector machine with integer parameters

Davide Anguita, Sandro Ridella, Alessandro Ghio, 2008, Neurocomputing.

Differential privacy and generalization: Sharper bounds with applications

Davide Anguita, Luca Oneto, Sandro Ridella, 2017, Pattern Recognit. Lett..

In-sample model selection for Support Vector Machines

Davide Anguita, Luca Oneto, Sandro Ridella, 2011, The 2011 International Joint Conference on Neural Networks.

Ship efficiency forecast based on sensors data collection: Improving numerical models through data analytics

Davide Anguita, Luca Oneto, Francesco Baldi, 2015, OCEANS 2015 - Genova.

Maximal Discrepancy vs. Rademacher Complexity for error estimation

Davide Anguita, Luca Oneto, Sandro Ridella, 2011, ESANN.

Crash Stop Maneuvering Performance Prediction: a Data-Driven Solution for Safety and Collision Avoidance

Davide Anguita, Luca Oneto, Andrea Coraddu, 2018 .

Smartphone battery saving by bit-based hypothesis spaces and local Rademacher Complexities

Davide Anguita, Luca Oneto, Sandro Ridella, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Training support vector machines: a quantum-computing perspective

Davide Anguita, Sandro Ridella, Rodolfo Zunino, 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

A support vector machine classifier from a bit-constrained, sparse and localized hypothesis space

Davide Anguita, Luca Oneto, Sandro Ridella, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

SLT-Based ELM for Big Social Data Analysis

Davide Anguita, Luca Oneto, Erik Cambria, 2017, Cognitive Computation.

Maximal Discrepancy for Support Vector Machines

Davide Anguita, Sandro Ridella, Alessandro Ghio, 2011, ESANN.

Vessel monitoring and design in industry 4.0: A data driven perspective

Davide Anguita, Luca Oneto, Andrea Coraddu, 2016, 2016 IEEE 2nd International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI).

Tuning the Distribution Dependent Prior in the PAC-Bayes Framework based on Empirical Data

Davide Anguita, Luca Oneto, Sandro Ridella, 2016, ESANN.

A dynamic, interpretable, and robust hybrid data analytics system for train movements in large-scale railway networks

Davide Anguita, Luca Oneto, Simone Petralli, 2019, International Journal of Data Science and Analytics.

Neural structures for visual motion tracking

Davide Anguita, Rodolfo Zunino, Giancarlo Parodi, 1995 .

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

Davide Anguita, Luca Oneto, Renzo Canepa, 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Advanced Analytics for Train Delay Prediction Systems by Including Exogenous Weather Data

Davide Anguita, Luca Oneto, Renzo Canepa, 2016, 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

Spectral Analysis of Electricity Demand Using Hilbert–Huang Transform

Davide Anguita, Joaquin Luque, Robert Denda, 2020, Sensors.

A Learning Analytics Approach to Correlate the Academic Achievements of Students with Interaction Data from an Educational Simulator

Davide Anguita, Luca Oneto, Matthias Rauterberg, 2015, EC-TEL.

Cavitation Noise Spectra Prediction with Hybrid Models

Davide Anguita, Luca Oneto, Giorgio Tani, 2019, INNSBDDL.

A Survey of old and New Results for the Test Error Estimation of a Classifier

Davide Anguita, Sandro Ridella, Alessandro Ghio, 2013, J. Artif. Intell. Soft Comput. Res..

Evaluating the Generalization Ability of Support Vector Machines through the Bootstrap

Davide Anguita, Andrea Boni, Sandro Ridella, 2000, Neural Processing Letters.

Energy Efficient Smartphone-Based Activity Recognition using Fixed-Point Arithmetic

Davide Anguita, Luca Oneto, Alessandro Ghio, 2013, J. Univers. Comput. Sci..

Statistical Learning Theory and ELM for Big Social Data Analysis

Davide Anguita, Luca Oneto, Erik Cambria, 2016, IEEE Computational Intelligence Magazine.

Sequential Networks as Finite State Machines

Davide Anguita, Luca Oneto, Domenico Ponta, 2019 .

Improved neural network for SVM learning

Davide Anguita, Andrea Boni, D. Anguita, 2002, IEEE Trans. Neural Networks.

Associative structures for vision

Davide Anguita, Rodolfo Zunino, Giancarlo Parodi, 1994, Multidimens. Syst. Signal Process..

Human Activity Recognition on Smartphones Using a Multiclass Hardware-Friendly Support Vector Machine

Davide Anguita, Luca Oneto, Alessandro Ghio, 2012, IWAAL.

The ISAAC server: a proposal for smart algorithms delivering

Davide Anguita, Fabio Rivieccio, Anna Marina Scapolla, 2003 .

Out-of-Sample Error Estimation: The Blessing of High Dimensionality

Davide Anguita, Luca Oneto, Sandro Ridella, 2014, 2014 IEEE International Conference on Data Mining Workshop.

Introduction to Sequential Networks

Davide Anguita, Luca Oneto, Domenico Ponta, 2019 .

K-Fold Generalization Capability Assessment for

Davide Anguita, Sandro Ridella, 2005 .

Visual Analytics for Supporting Conflict Resolution in Large Railway Networks

Daniel A. Keim, Davide Anguita, Luca Oneto, 2019, INNSBDDL.

Digital Least Squares Support Vector Machines

Davide Anguita, Andrea Boni, 2004, Neural Processing Letters.

Train Delay Prediction Systems: A Big Data Analytics Perspective

Davide Anguita, Luca Oneto, Renzo Canepa, 2017, Big Data Res..

Random Forests Model Selection

Davide Anguita, Luca Oneto, Ilenia Orlandi, 2016, ESANN.

Design and implementation of HDL modules and circuits for underwater optical wireless communication

Davide Anguita, Davide Brizzolara, Giancarlo Parodi, 2010, ICT 2010.

Improving Railway Maintenance Actions with Big Data and Distributed Ledger Technologies

Davide Anguita, Luca Oneto, Marie Swiatek, 2019, INNSBDDL.

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

Davide Anguita, Luca Oneto, Massimo Figari, 2016 .

Measuring the Expressivity of Graph Kernels through the Rademacher Complexity

Alessandro Sperduti, Davide Anguita, Luca Oneto, 2016, ESANN.

Local Rademacher Complexity: Sharper risk bounds with and without unlabeled samples

Davide Anguita, Luca Oneto, Sandro Ridella, 2015, Neural Networks.

High Performance Neurocomputing: Industrial and Medical Applications of the RAIN System

Davide Anguita, Andrea Boni, Marco Chirico, 1998, HPCN Europe.

Measuring the expressivity of graph kernels through Statistical Learning Theory

Alessandro Sperduti, Davide Anguita, Luca Oneto, 2017, Neurocomputing.

Introduction to FPGA and HDL Design

Davide Anguita, Luca Oneto, Domenico Ponta, 2019 .

Learning Hardware Friendly Classifiers Through Algorithmic Risk Minimization

Davide Anguita, Luca Oneto, L. Oneto, 2015, Advances in Neural Networks.

An improved analysis of the Rademacher data-dependent bound using its self bounding property

Davide Anguita, Luca Oneto, Sandro Ridella, 2013, Neural Networks.

Constraint-Aware Data Analysis on Mobile Devices: An Application to Human Activity Recognition on Smartphones

Davide Anguita, Luca Oneto, J. L. Ortiz, 2017 .

A learning machine for resource-limited adaptive hardware

Davide Anguita, Alessandro Ghio, Stefano Pischiutta, 2007, Second NASA/ESA Conference on Adaptive Hardware and Systems (AHS 2007).

VHDL modeling of PHY and MAC Layer modules for underwater optical wireless communication

Davide Anguita, Davide Brizzolara, Giancarlo Parodi, 2010, Proceedings of Papers 5th European Conference on Circuits and Systems for Communications (ECCSC'10).

Incorporating a priori knowledge into neural networks

Davide Anguita, Sandro Ridella, Rodolfo Zunino, 1995 .

Semi-supervised Learning for Affective Common-Sense Reasoning

Davide Anguita, Luca Oneto, Erik Cambria, 2017, Cognitive Computation.

Transputer-based architectures for associative image classification

Davide Anguita, Rodolfo Zunino, Giancarlo Parodi, 1991, Proceedings of the Third IEEE Symposium on Parallel and Distributed Processing.

Dropout Prediction at University of Genoa: a Privacy Preserving Data Driven Approach

Davide Anguita, Luca Oneto, Gianvittorio Luria, 2017, ESANN.

A Public Domain Dataset for Human Activity Recognition using Smartphones

Davide Anguita, Luca Oneto, Alessandro Ghio, 2013, ESANN.

Fast training of Support Vector Machines for regression

Davide Anguita, Andrea Boni, Stefano Pace, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Towards analog and digital hardware for support vector machines

Davide Anguita, Andrea Boni, D. Anguita, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

An efficient implementation of BP on RISC-based workstations

Davide Anguita, Rodolfo Zunino, Giancarlo Parodi, 1994, Neurocomputing.

Fully Empirical and Data-Dependent Stability-Based Bounds

Davide Anguita, Luca Oneto, Sandro Ridella, 2015, IEEE Transactions on Cybernetics.

SVM learning with fixed-point math

Davide Anguita, Andrea Boni, Sandro Ridella, 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis

Davide Anguita, Luca Oneto, Sandro Ridella, 2016, Pattern Recognit. Lett..

Multilayer Graph Node Kernels: Stacking While Maintaining Convexity

Alessandro Sperduti, Davide Anguita, Luca Oneto, 2018, Neural Processing Letters.

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

Davide Anguita, Andrea Boni, Sandro Ridella, 2003, IEEE Trans. Neural Networks.

Machine learning for wear forecasting of naval assets for condition-based maintenance applications

Davide Anguita, Luca Oneto, Alessandro Ghio, 2015, 2015 International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles (ESARS).

Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels

Alessandro Sperduti, Davide Anguita, Luca Oneto, 2018, IEEE Transactions on Neural Networks and Learning Systems.

Understanding Violin Players’ Skill Level Based on Motion Capture: a Data-Driven Perspective

Davide Anguita, Luca Oneto, Antonio Camurri, 2020, Cognitive Computation.

Hyperparameter design criteria for support vector classifiers

Davide Anguita, Sandro Ridella, Rodolfo Zunino, 2003, Neurocomputing.

Human Activity and Motion Disorder Recognition: towards smarter Interactive Cognitive Environments

Davide Anguita, Alessandro Ghio, Andreu Català, 2013, ESANN.

Learning in large neural networks

Davide Anguita, Rodolfo Zunino, Filippo Passaggio, 1995, HPCN Europe.

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

Davide Anguita, Davide Brizzolara, Giancarlo Parodi, 2009, 2009 Third International Conference on Sensor Technologies and Applications.

In-sample Model Selection for Trimmed Hinge Loss Support Vector Machine

Davide Anguita, Luca Oneto, Sandro Ridella, 2012, Neural Processing Letters.

The Finite State Machine as System Controller

Davide Anguita, Luca Oneto, Domenico Ponta, 2019 .

An Algorithm for Reducing the Number of Support Vectors

Davide Anguita, Sandro Ridella, Fabio Rivieccio, 2004, WIRN.

SVM performance assessment for the control of injection moulding processes and plasticating extrusion

Davide Anguita, Andrea Boni, L. Tagliafico, 2002, Int. J. Syst. Sci..

Model Selection for Big Data: Algorithmic Stability and Bag of Little Bootstraps on GPUs

Davide Anguita, Luca Oneto, Alessandro Ghio, 2015, ESANN.

The 'K' in K-fold Cross Validation

Davide Anguita, Luca Oneto, Sandro Ridella, 2012, ESANN.

A VLSI friendly algorithm for support vector machines

Davide Anguita, Andrea Boni, Sandro Ridella, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Condition-Based Maintenance of Naval Propulsion Systems with supervised Data Analysis

Davide Anguita, Luca Oneto, Alan J. Murphy, 2018 .

Data Mining Tools: From Web to Grid Architectures

Davide Anguita, Fabio Rivieccio, Anna Marina Scapolla, 2005, EGC.

Selecting the hypothesis space for improving the generalization ability of Support Vector Machines

Davide Anguita, Luca Oneto, Sandro Ridella, 2011, The 2011 International Joint Conference on Neural Networks.

Unintrusive Monitoring of Induction Motors Bearings via Deep Learning on Stator Currents

Davide Anguita, Luca Oneto, Andrea Coraddu, 2018, INNS Conference on Big Data.

Smart Plankton: a Nature Inspired Underwater Wireless Sensor Network

Davide Anguita, Alessandro Ghio, Davide Brizzolara, 2008, 2008 Fourth International Conference on Natural Computation.

Learning analytics for Lix puzzle-game

Davide Anguita, Matthias Rauterberg, Maira B. Carvalho, 2017 .

Advances in Learning with Kernels: Theory and Practice in a World of growing Constraints

Davide Anguita, Luca Oneto, Fabio Aiolli, 2016, ESANN.

Restoration Time Prediction in Large Scale Railway Networks: Big Data and Interpretability

Davide Anguita, Luca Oneto, Simone Petralli, 2019, INNSBDDL.

Object Oriented Design of a Simulator for Large BP Neural Networks

Jean-Marc Adamo, Davide Anguita, J. Adamo, 1995, IWANN.

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

Davide Anguita, Luca Oneto, Sandro Ridella, 2012, IEEE Transactions on Neural Networks and Learning Systems.

Optical communication for Underwater Wireless Sensor Networks: a VHDL-implementation of a Physical Layer 802.15.4 compatible

Davide Anguita, Davide Brizzolara, Giancarlo Parodi, 2009, OCEANS 2009-EUROPE.

Nested Sequential Minimal Optimization for Support Vector Machines

Davide Anguita, Luca Oneto, Sandro Ridella, 2012, ICANN.

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

Davide Anguita, Luca Oneto, Emanuele Fumeo, 2015, INNS Conference on Big Data.

A local Vapnik-Chervonenkis complexity

Davide Anguita, Luca Oneto, Sandro Ridella, 2016, Neural Networks.

Support vector machines and strictly positive definite kernel: The regularization hyperparameter is more important than the kernel hyperparameters

Davide Anguita, Luca Oneto, Sandro Ridella, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Train Overtaking Prediction in Railway Networks: A Big Data Perspective

Davide Anguita, Luca Oneto, Simone Petralli, 2019, INNSBDDL.

Boolean Algebra and Combinational Logic

Davide Anguita, Luca Oneto, Domenico Ponta, 2019 .

Advances in learning analytics and educational data mining

Davide Anguita, Luca Oneto, Matthias Rauterberg, 2015, ESANN.

The Effect ofQuantization on Support Vector Machines with GaussianKernel

Davide Anguita, Giovanni Bozza, 2005 .

Mining Big Data with Random Forests

Davide Anguita, Luca Oneto, Alessandro Lulli, 2018, Cognitive Computation.

Crack random forest for arbitrary large datasets

Davide Anguita, Luca Oneto, Alessandro Lulli, 2017, 2017 IEEE International Conference on Big Data (Big Data).

Quantum computing and supervised machine learning

Davide Anguita, Luca Oneto, Sandro Ridella, 2017 .

Delay Prediction System for Large-Scale Railway Networks Based on Big Data Analytics

Davide Anguita, Luca Oneto, Renzo Canepa, 2016, INNS Conference on Big Data.

Flip-Flop-Based Synchronous Networks

Davide Anguita, Luca Oneto, Domenico Ponta, 2019 .

A heterogeneous and reconfigurable machine-vision system

Vito Di Gesù, Davide Anguita, Gaetano Gerardi, 1995 .

Operational profiles data analytics for ship design improvement

Davide Anguita, Luca Oneto, Andrea Coraddu, 2016 .

Shared-memory architecture to implement a high-connectivity processing node

Davide Anguita, Rodolfo Zunino, F. Ancona, 1995 .

Human Algorithmic Stability and Human Rademacher Complexity

Davide Anguita, Luca Oneto, Matthias Rauterberg, 2015, ESANN.

Shrinkage learning to improve SVM with hints

Davide Anguita, Luca Oneto, Sandro Ridella, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Unsupervised clustering and the capacity of support vector machines

Davide Anguita, Sandro Ridella, Rodolfo Zunino, 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

Smart plankton - a new generation of underwater wireless sensor network

Davide Anguita, Alessandro Ghio, Davide Brizzolara, 2008, ALIFE.

Tikhonov, Ivanov and Morozov regularization for support vector machine learning

Davide Anguita, Luca Oneto, Sandro Ridella, 2015, Machine Learning.

Performance assessment and uncertainty quantification of predictive models for smart manufacturing systems

Davide Anguita, Luca Oneto, Ilenia Orlandi, 2015, 2015 IEEE International Conference on Big Data (Big Data).

Optimizing Fuel Consumption in Thrust Allocation for Marine Dynamic Positioning Systems

Davide Anguita, Luca Oneto, Andrea Coraddu, 2021, IEEE Transactions on Automation Science and Engineering.

Toward Learning Trustworthily from Data Combining Privacy, Fairness, and Explainability: An Application to Face Recognition

Davide Anguita, Luca Oneto, Nicolò Navarin, 2021, Entropy.

Learn and Visually Explain Deep Fair Models: an Application to Face Recognition

Davide Anguita, Luca Oneto, Nicolò Navarin, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Keep it Simple: Handcrafting Feature and Tuning Random Forests and XGBoost to face the Affective Movement Recognition Challenge 2021

Davide Anguita, Luca Oneto, Antonio Camurri, 2021, 2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW).

Deep fair models for complex data: Graphs labeling and explainable face recognition

Davide Anguita, Luca Oneto, Nicolò Navarin, 2021, Neurocomputing.

Circuital implementation of support vector machines

Davide Anguita, Sandro Ridella, Stefano Rovetta, 1998 .