Sandro Ridella

ORCID

Publication Activity (10 Years)

Years Active: 1986-2024
Publications (10 Years): 20

Top Venues

ESANN

Neurocomputing

IJCNN

Pattern Recognit. Lett.

Publications

Luca Oneto, Sandro Ridella, Davide Anguita
Towards algorithms and models that we can trust: A theoretical perspective. Neurocomputing 592 (2024)
Luca Oneto, Sandro Ridella, Davide Anguita
Do we really need a new theory to understand over-parameterization? Neurocomputing 543 (2023)
Luca Oneto, Sandro Ridella, Davide Anguita
Towards Randomized Algorithms and Models that We Can Trust: a Theoretical Perspective. ESANN (2023)
Luca Oneto, Sandro Ridella, Davide Anguita
Do We Really Need a New Theory to Understand the Double-Descent? ESANN (2022)
Luca Oneto, Sandro Ridella, Davide Anguita
The benefits of adversarial defense in generalization. Neurocomputing 505 (2022)
Luca Oneto, Sandro Ridella
Distribution-Dependent Weighted Union Bound. Entropy 23 (1) (2021)
Luca Oneto, Sandro Ridella, Davide Anguita
The Benefits of Adversarial Defence in Generalisation. ESANN (2021)
Luca Oneto, Sandro Ridella, Davide Anguita
Improving the Union Bound: a Distribution Dependent Approach. ESANN (2020)
Luca Oneto, Sandro Ridella, Davide Anguita
Local Rademacher Complexity Machine. Neurocomputing 342 (2019)
Luca Oneto, Nicolò Navarin, Michele Donini, Sandro Ridella, Alessandro Sperduti, Fabio Aiolli, Davide Anguita
Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels. IEEE Trans. Neural Networks Learn. Syst. 29 (10) (2018)
Luca Oneto, Sandro Ridella, Davide Anguita
Local Rademacher Complexity Machine. ESANN (2018)
Luca Oneto, Francesca Cipollini, Sandro Ridella, Davide Anguita
Randomized learning: Generalization performance of old and new theoretically grounded algorithms. Neurocomputing 298 (2018)
Luca Oneto, Sandro Ridella, Davide Anguita
Differential privacy and generalization: Sharper bounds with applications. Pattern Recognit. Lett. 89 (2017)
Luca Oneto, Sandro Ridella, Davide Anguita
Generalization Performances of Randomized Classifiers and Algorithms built on Data Dependent Distributions. ESANN (2017)
Luca Oneto, Davide Anguita, Sandro Ridella
A local Vapnik-Chervonenkis complexity. Neural Networks 82 (2016)
Luca Oneto, Sandro Ridella, Davide Anguita
Tuning the Distribution Dependent Prior in the PAC-Bayes Framework based on Empirical Data. ESANN (2016)
Luca Oneto, Sandro Ridella, Davide Anguita
Learning Hardware-Friendly Classifiers Through Algorithmic Stability. ACM Trans. Embed. Comput. Syst. 15 (2) (2016)
Luca Oneto, Sandro Ridella, Davide Anguita
Tikhonov, Ivanov and Morozov regularization for support vector machine learning. Mach. Learn. 103 (1) (2016)
Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita
Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates. Neural Process. Lett. 43 (2) (2016)
Luca Oneto, Davide Anguita, Sandro Ridella
PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis. Pattern Recognit. Lett. 80 (2016)
Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita
Fast convergence of extended Rademacher Complexity bounds. IJCNN (2015)
Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita
Support vector machines and strictly positive definite kernel: The regularization hyperparameter is more important than the kernel hyperparameters. IJCNN (2015)
Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita
Fully Empirical and Data-Dependent Stability-Based Bounds. IEEE Trans. Cybern. 45 (9) (2015)
Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita
Local Rademacher Complexity: Sharper risk bounds with and without unlabeled samples. Neural Networks 65 (2015)
Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita
Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency. Neurocomputing 169 (2015)
Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita
Shrinkage learning to improve SVM with hints. IJCNN (2015)
Luca Oneto, Alessandro Ghio, Sandro Ridella, Jorge Luis Reyes-Ortiz, Davide Anguita
Out-of-Sample Error Estimation: The Blessing of High Dimensionality. ICDM Workshops (2014)
Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella
Unlabeled patterns to tighten Rademacher complexity error bounds for kernel classifiers. Pattern Recognit. Lett. 37 (2014)
Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella
Learning with few bits on small-scale devices: From regularization to energy efficiency. ESANN (2014)
Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella
Smartphone battery saving by bit-based hypothesis spaces and local Rademacher Complexities. IJCNN (2014)
Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella
A Deep Connection Between the Vapnik-Chervonenkis Entropy and the Rademacher Complexity. IEEE Trans. Neural Networks Learn. Syst. 25 (12) (2014)
Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella
A support vector machine classifier from a bit-constrained, sparse and localized hypothesis space. IJCNN (2013)
Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella
A Learning Machine with a Bit-Based Hypothesis Space. ESANN (2013)
Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella
Some results about the Vapnik-Chervonenkis entropy and the rademacher complexity. IJCNN (2013)
Luca Oneto, Alessandro Ghio, Davide Anguita, Sandro Ridella
An improved analysis of the Rademacher data-dependent bound using its self bounding property. Neural Networks 44 (2013)
Davide Anguita, Luca Ghelardoni, Alessandro Ghio, Sandro Ridella
A Survey of old and New Results for the Test Error Estimation of a Classifier. J. Artif. Intell. Soft Comput. Res. 3 (4) (2013)
Davide Anguita, Alessandro Ghio, Luca Oneto, Jorge Luis Reyes-Ortiz, Sandro Ridella
A Novel Procedure for Training L1-L2 Support Vector Machine Classifiers. ICANN (2013)
Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella
In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines. IEEE Trans. Neural Networks Learn. Syst. 23 (9) (2012)
Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella
In-sample Model Selection for Trimmed Hinge Loss Support Vector Machine. Neural Process. Lett. 36 (3) (2012)
Luca Oneto, Davide Anguita, Alessandro Ghio, Sandro Ridella
Rademacher Complexity and Structural Risk Minimization: An Application to Human Gene Expression Datasets. ICANN (2) (2012)
Sergio Decherchi, Mauro Parodi, Sandro Ridella
Learning the mean: A neural network approach. Neurocomputing 77 (1) (2012)
Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella
Structural Risk Minimization and Rademacher Complexity for Regression. ESANN (2012)
Davide Anguita, Luca Ghelardoni, Alessandro Ghio, Luca Oneto, Sandro Ridella
The 'K' in K-fold Cross Validation. ESANN (2012)
Alessandro Ghio, Davide Anguita, Luca Oneto, Sandro Ridella, Carlotta Schatten
Nested Sequential Minimal Optimization for Support Vector Machines. ICANN (2) (2012)
Davide Anguita, Alessandro Ghio, Sandro Ridella
Maximal Discrepancy for Support Vector Machines. Neurocomputing 74 (9) (2011)
Davide Anguita, Luca Carlino, Alessandro Ghio, Sandro Ridella
A FPGA Core Generator for Embedded Classification Systems. J. Circuits Syst. Comput. 20 (2) (2011)
Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella
In-sample model selection for Support Vector Machines. IJCNN (2011)
Luca Oneto, Davide Anguita, Alessandro Ghio, Sandro Ridella
The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers. NIPS (2011)
Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella
Maximal Discrepancy vs. Rademacher Complexity for error estimation. ESANN (2011)
Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella
Selecting the hypothesis space for improving the generalization ability of Support Vector Machines. IJCNN (2011)
Davide Anguita, Luca Ghelardoni, Alessandro Ghio, Sandro Ridella
Test error bounds for classifiers: A survey of old and new results. FOCI (2011)
Davide Anguita, Alessandro Ghio, Sandro Ridella
Maximal Discrepancy for Support Vector Machines. ESANN (2010)
Davide Anguita, Alessandro Ghio, Noemi Greco, Luca Oneto, Sandro Ridella
Model selection for support vector machines: Advantages and disadvantages of the Machine Learning Theory. IJCNN (2010)
Sergio Decherchi, Mauro Parodi, Sandro Ridella
A neural model approach for regularization in the mean estimation case. IJCNN (2010)
Sergio Decherchi, Sandro Ridella, Rodolfo Zunino, Paolo Gastaldo, Davide Anguita
Using unsupervised analysis to constrain generalization bounds for support vector classifiers. IEEE Trans. Neural Networks 21 (3) (2010)
Davide Anguita, Alessandro Ghio, Sandro Ridella, Dario Sterpi
K-Fold Cross Validation for Error Rate Estimate in Support Vector Machines. DMIN (2009)
Enrique Alba, Davide Anguita, Alessandro Ghio, Sandro Ridella
Using Variable Neighborhood Search to improve the Support Vector Machine performance in embedded automotive applications. IJCNN (2008)
Davide Anguita, Alessandro Ghio, Stefano Pischiutta, Sandro Ridella
A support vector machine with integer parameters. Neurocomputing 72 (1-3) (2008)
Davide Anguita, Alessandro Ghio, Stefano Pischiutta, Sandro Ridella
A Hardware-friendly Support Vector Machine for Embedded Automotive Applications. IJCNN (2007)
Davide Anguita, Stefano Pischiutta, Sandro Ridella, Dario Sterpi
Feed-Forward Support Vector Machine Without Multipliers. IEEE Trans. Neural Networks 17 (5) (2006)
Paolo Gastaldo, Sandro Ridella, Rodolfo Zunino
Prospects of quantum-classical optimization for digital design. Appl. Math. Comput. 179 (2) (2006)
Davide Anguita, Sandro Ridella, Dario Sterpi
Testing the Augmented Binary Multiclass SVM on Microarray Data. IJCNN (2006)
Davide Anguita, Sandro Ridella, Fabio Rivieccio
An Algorithm for Reducing the Number of Support Vectors. WIRN (2004)
Sandro Ridella, Rodolfo Zunino
Using K-Winner Machines for domain analysis. Neurocomputing 62 (2004)
Davide Anguita, Andrea Boni, Sandro Ridella
A digital architecture for support vector machines: theory, algorithm, and FPGA implementation. IEEE Trans. Neural Networks 14 (5) (2003)
Davide Anguita, Sandro Ridella, Fabio Rivieccio, Rodolfo Zunino
Hyperparameter design criteria for support vector classifiers. Neurocomputing 55 (1-2) (2003)
Davide Anguita, Sandro Ridella, Fabio Rivieccio, Rodolfo Zunino
Quantum optimization for training support vector machines. Neural Networks 16 (5-6) (2003)
Massimiliano Bracco, Sandro Ridella, Rodolfo Zunino
Digital implementation of hierarchical vector quantization. IEEE Trans. Neural Networks 14 (5) (2003)
Davide Anguita, Sandro Ridella, Fabio Rivieccio, Rodolfo Zunino
Automatic Hyperparameter Tuning for Support Vector Machines. ICANN (2002)
Sandro Ridella, Stefano Rovetta, Rodolfo Zunino
K-winner machines for pattern classification. IEEE Trans. Neural Networks 12 (2) (2001)
Sandro Ridella, Rodolfo Zunino
Empirical measure of multiclass generalization performance: the K-winner machine case. IEEE Trans. Neural Networks 12 (6) (2001)
Sandro Ridella, Stefano Rovetta, Rodolfo Zunino
The K-Winner Machine Model. IJCNN (1) (2000)
Sandro Ridella, Stefano Rovetta, Rodolfo Zunino
Augmenting vector quantization with interval arithmetics for image-coding applications. ISCAS (2000)
Davide Anguita, Andrea Boni, Sandro Ridella
Evaluating the Generalization Ability of Support Vector Machines through the Bootstrap. Neural Process. Lett. 11 (1) (2000)
Davide Anguita, Andrea Boni, Sandro Ridella
Digital VLSI Algorithms and Architectures for Support Vector Machines. Int. J. Neural Syst. 10 (3) (2000)
Sandro Ridella, Stefano Rovetta, Rodolfo Zunino
Representation and generalization properties of class-entropy networks. IEEE Trans. Neural Networks 10 (1) (1999)
Gian Paolo Drago, Sandro Ridella
Possibility and Necessity Pattern Classification using an Interval Arithmetic Perceptron. Neural Comput. Appl. 8 (1) (1999)
Davide Anguita, Andrea Boni, Sandro Ridella
A VLSI friendly algorithm for support vector machines. IJCNN (1999)
Sandro Ridella, Stefano Rovetta, Rodolfo Zunino
Circular backpropagation networks embed vector quantization. IEEE Trans. Neural Networks 10 (4) (1999)
Davide Anguita, Andrea Boni, Sandro Ridella
Support Vector Machines: A Comparison of Some Kernel Functions. IIA/SOCO (1999)
Davide Anguita, Sandro Ridella, Stefano Rovetta
Worst case analysis of weight inaccuracy effects in multilayer perceptrons. IEEE Trans. Neural Networks 10 (2) (1999)
Sandro Ridella, Stefano Rovetta, Rodolfo Zunino
Plastic Algorithm for Adaptive Vector Quantisation. Neural Comput. Appl. 7 (1) (1998)
Gian Paolo Drago, Sandro Ridella
Pruning with interval arithmetic perceptron. Neurocomputing 18 (1-3) (1998)
Fabio Ancona, Sandro Ridella, Stefano Rovetta, Rodolfo Zunino
On the importance of sorting in "neural gas" training of vector quantizers. ICNN (1997)
Sandro Ridella, Stefano Rovetta, Rodolfo Zunino
CBP networks as a generalized neural model. ICNN (1997)
Sandro Ridella, Stefano Rovetta, Rodolfo Zunino
Circular backpropagation networks for classification. IEEE Trans. Neural Networks 8 (1) (1997)
Gian Paolo Drago, Sandro Ridella
On the convergence of a growing topology neural algorithm. Neurocomputing 12 (2-3) (1996)
Davide Anguita, Sandro Ridella, Stefano Rovetta, Rodolfo Zunino
Limiting the effects of weight errors in feedforward networks using interval arithmetic. ICNN (1996)
Sandro Ridella, Stefano Rovetta, Rodolfo Zunino
Learning the appropriate representation paradigm by circular processing units. ESANN (1995)
Sandro Ridella, Stefano Rovetta, Rodolfo Zunino
Adaptive Internal Representation in Circular Back-Propagation Networks. Neural Comput. Appl. 3 (4) (1995)
Gian Paolo Drago, Mauro Morando, Sandro Ridella
An Adaptive Momentum Back Propagation (AMBP). Neural Comput. Appl. 3 (4) (1995)
Gian Paolo Drago, Sandro Ridella
Convergence Properties of Cascade Correlation in Function Approximation. Neural Comput. Appl. 2 (3) (1994)
Sandro Ridella, Gian Luca Speroni, Paolo Trebino, Rodolfo Zunino
Class-Entropy Minimisation Networks for Domain Analysis and Rule Extraction. Neural Comput. Appl. 2 (1) (1994)
Sandro Ridella, Gian Luca Speroni, Paolo Trebino, Rodolfo Zunino
Pruning and rule extraction using class entropy. ICNN (1993)
Giancarlo Parodi, Sandro Ridella, Rodolfo Zunino
Using chaos to generate keys for associative noise-like coding memories. Neural Networks 6 (4) (1993)
Alessandro De Gloria, Paolo Faraboschi, Sandro Ridella
A dedicated massively parallel architecture for the Boltzmann machine. Parallel Comput. 18 (1) (1992)
Gian Paolo Drago, Sandro Ridella
Statistically controlled activation weight initialization (SCAWI). IEEE Trans. Neural Networks 3 (4) (1992)
Marco Muselli, Sandro Ridella
Global Optimization of Functions with the Interval Genetic Algorithm. Complex Syst. 6 (3) (1992)
Angelo Corana, Aldo Casaleggio, Claudia Rolando, Sandro Ridella
Efficient computation of the correlation dimension from a time series on a LIW computer. Parallel Comput. 17 (6-7) (1991)
Angelo Corana, Claudio Martini, Sandro Ridella
Corrigenda: "Minimizing Multimodal Functions of Continuous Variables with the 'Simulated Annealing' Algorithm". ACM Trans. Math. Softw. 15 (3) (1989)

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Publication Activity (10 Years)

Top Topics

Top Venues

Sandro Ridella