S. Ridella

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Aliases
S Ridella, S. Ridella, Sandro Ridella
Publication record
201 papers · 4,984 citations · H-index 31

PAPERS

Reconciling grokking with statistical learning theory through the lens of norm- and stability-based generalization bounds
20260 citationsauthor #2
Reconciling Grokking with Statistical Learning Theory
20251 citationsauthor #2
Informed Machine Learning: Excess risk and generalization
20257 citationsauthor #2
Towards algorithms and models that we can trust: A theoretical perspective
20247 citationsauthor #2
Informed Machine Learning: Excess Risk and Generalization
20243 citationsauthor #3
Towards Randomized Algorithms and Models that We Can Trust: a Theoretical Perspective
20231 citationsauthor #2
Do we really need a new theory to understand over-parameterization?
202327 citationsauthor #2
Do We Really Need a New Theory to Understand the Double-Descent?
20221 citationsauthor #2
The benefits of adversarial defense in generalization
20226 citationsauthor #2
The Benefits of Adversarial Defence in Generalisation
20211 citationsauthor #2
Distribution-Dependent Weighted Union Bound †
20210 citationsauthor #2
Improving the Union Bound: a Distribution Dependent Approach
20201 citationsauthor #2
Local Rademacher Complexity Machine
20194 citationsauthor #2
Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels
201811 citationsauthor #4
Randomized learning: Generalization performance of old and new theoretically grounded algorithms
20185 citationsauthor #3
Quantum computing and supervised machine learning
20171 citationsauthor #2
Differential privacy and generalization: Sharper bounds with applications
201738 citationsauthor #2
Generalization Performances of Randomized Classifiers and Algorithms built on Data Dependent Distributions
20172 citationsauthor #2
PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis
201626 citationsauthor #3
A local Vapnik-Chervonenkis complexity
201615 citationsauthor #3
Tuning the Distribution Dependent Prior in the PAC-Bayes Framework based on Empirical Data
20165 citationsauthor #2
Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates
201629 citationsauthor #3
Tikhonov, Ivanov and Morozov regularization for support vector machine learning
201668 citationsauthor #2
Learning Hardware-Friendly Classifiers Through Algorithmic Stability
20168 citationsauthor #2
Fully Empirical and Data-Dependent Stability-Based Bounds
201539 citationsauthor #3
Fast convergence of extended Rademacher Complexity bounds
20151 citationsauthor #3
Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates
20150 citationsauthor #3
Local Rademacher Complexity: Sharper risk bounds with and without unlabeled samples
201542 citationsauthor #3
Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency
201517 citationsauthor #3
Tikhonov, Ivanov and Morozov regularization for support vector machine learning
201521 citationsauthor #2
Support vector machines and strictly positive definite kernel: The regularization hyperparameter is more important than the kernel hyperparameters
201517 citationsauthor #3
Shrinkage learning to improve SVM with hints
20152 citationsauthor #3
Unlabeled patterns to tighten Rademacher complexity error bounds for kernel classifiers
201413 citationsauthor #4
Learning with few bits on small-scale devices: From regularization to energy efficiency
20141 citationsauthor #4
A Deep Connection Between the Vapnik–Chervonenkis Entropy and the Rademacher Complexity
201421 citationsauthor #4
Out-of-Sample Error Estimation: The Blessing of High Dimensionality
20143 citationsauthor #3
Smartphone battery saving by bit-based hypothesis spaces and local Rademacher Complexities
20145 citationsauthor #4
A Novel Procedure for Training L1-L2 Support Vector Machine Classifiers
20132 citationsauthor #5
Some results about the Vapnik-Chervonenkis entropy and the rademacher complexity
20131 citationsauthor #4
A Survey of old and New Results for the Test Error Estimation of a Classifier
20139 citationsauthor #4
An improved analysis of the Rademacher data-dependent bound using its self bounding property
201320 citationsauthor #4
A Learning Machine with a Bit-Based Hypothesis Space
201313 citationsauthor #4
A support vector machine classifier from a bit-constrained, sparse and localized hypothesis space
20138 citationsauthor #4
Nested Sequential Minimal Optimization for Support Vector Machines
20125 citationsauthor #4
Structural Risk Minimization and Rademacher Complexity for Regression
20122 citationsauthor #4
In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines
2012109 citationsauthor #4
In-sample Model Selection for Trimmed Hinge Loss Support Vector Machine
20120 citationsauthor #4
Learning the mean: A neural network approach
20124 citationsauthor #3
In-sample Model Selection for Trimmed Hinge Loss Support Vector Machine
201217 citationsauthor #4
Rademacher Complexity and Structural Risk Minimization: An Application to Human Gene Expression Datasets
20121 citationsauthor #4
The 'K' in K-fold Cross Validation
2012344 citationsauthor #5
Selecting the hypothesis space for improving the generalization ability of Support Vector Machines
201125 citationsauthor #4
Maximal Discrepancy vs. Rademacher Complexity for error estimation
201117 citationsauthor #4
The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers
201125 citationsauthor #4
A FPGA Core Generator for Embedded Classification Systems
201131 citationsauthor #4
Test error bounds for classifiers: A survey of old and new results
20115 citationsauthor #4
In-sample model selection for Support Vector Machines
201135 citationsauthor #4
Maximal Discrepancy for Support Vector Machines
201122 citationsauthor #3
A neural model approach for regularization in the mean estimation case
20101 citationsauthor #3
Model selection for support vector machines: Advantages and disadvantages of the Machine Learning Theory
201097 citationsauthor #5
Using Unsupervised Analysis to Constrain Generalization Bounds for Support Vector Classifiers
201020 citationsauthor #2
K-Fold Cross Validation for Error Rate Estimate in Support Vector Machines
2009106 citationsauthor #3
Using Variable Neighborhood Search to improve the Support Vector Machine performance in embedded automotive applications
200810 citationsauthor #4
A support vector machine with integer parameters
200845 citationsauthor #4
Characterization of a cellular array of dipoles for molecular information processing
20080 citationsauthor #6
Explicit overall risk minimization transductive bound
20081 citationsauthor #3
A Hardware-friendly Support Vector Machine for Embedded Automotive Applications
200757 citationsauthor #4
Testing the Augmented Binary Multiclass SVM on Microarray Data
20063 citationsauthor #2
Prospects of quantum-classical optimization for digital design
20063 citationsauthor #2
Feed-Forward Support Vector Machine Without Multipliers
200673 citationsauthor #3
K-fold generalization capability assessment for support vector classifiers
200533 citationsauthor #2
K-Fold Generalization Capability Assessment for
20050 citationsauthor #2
Unsupervised clustering and the capacity of support vector machines
20044 citationsauthor #2
Model selection in top quark tagging with a support vector classifier
20048 citationsauthor #2
A new method for multiclass support vector machines
200428 citationsauthor #2
Using K-Winner Machines for domain analysis
20042 citationsauthor #1
Theoretical and Practical Model Selection Methods for Support Vector Classifiers
200451 citationsauthor #3
An Algorithm for Reducing the Number of Support Vectors
20043 citationsauthor #2
Quantum optimization for training support vector machines
200399 citationsauthor #2
Training support vector machines: a quantum-computing perspective
20039 citationsauthor #2
Hyperparameter design criteria for support vector classifiers
200360 citationsauthor #2
SVM learning with fixed-point math
20032 citationsauthor #3
Digital implementation of hierarchical vector quantization
200321 citationsauthor #2
A digital architecture for support vector machines: theory, algorithm, and FPGA implementation
2003211 citationsauthor #3
The Digital Kernel Perceptron
200210 citationsauthor #3
Automatic Hyperparameter Tuning for Support Vector Machines
200211 citationsauthor #2
Empirical measure of multiclass generalization performance: the K-winner machine case
20019 citationsauthor #1
Performance characterization of K-winner machines
20010 citationsauthor #1
K-winner machines for pattern classification
200141 citationsauthor #1
The K-Winner Machine model
20001 citationsauthor #1
Evaluating the Generalization Ability of Support Vector Machines through the Bootstrap
200049 citationsauthor #3
Digital VLSI Algorithms and Architectures for Support Vector Machines
20006 citationsauthor #3
Augmenting vector quantization with interval arithmetics for image-coding applications
20000 citationsauthor #1
IAVQ-interval-arithmetic vector quantization for image compression
200029 citationsauthor #1
Worst case analysis of weight inaccuracy effects in multilayer perceptrons
199921 citationsauthor #2
Representation and generalization properties of class-entropy networks
199912 citationsauthor #1
Support Vector Machines: A Comparison of Some Kernel Functions
19992 citationsauthor #3
Possibility and Necessity Pattern Classification using an Interval Arithmetic Perceptron
199919 citationsauthor #2
Convergence Properties of the Circular Cascade Correlation algorithm
19990 citationsauthor #2
A VLSI friendly algorithm for support vector machines
19995 citationsauthor #3

TIMELINE

1970 25 citations

1971 13 citations

1972 18 citations

1973 1 citations

1974 0 citations

1975 0 citations

1976 55 citations

1977 2 citations

1978 80 citations

1979 35 citations

1980 32 citations

1982 18 citations

1984 23 citations

1985 8 citations

1986 32 citations

1987 1,660 citations

1988 5 citations

1989 25 citations

1990 7 citations

1991 30 citations

1992 192 citations

1993 29 citations

1994 14 citations

1995 44 citations

1996 12 citations

1997 175 citations

1998 84 citations

1999 120 citations

2000 85 citations

2001 50 citations

2002 21 citations

2003 402 citations

2004 96 citations

2005 33 citations

2006 79 citations

2007 57 citations

2008 56 citations

2009 106 citations

2010 118 citations

2011 160 citations

2012 482 citations

2013 53 citations

2014 43 citations

2015 139 citations

2016 151 citations

2017 41 citations

2018 16 citations

2019 4 citations

2020 1 citations

2021 1 citations

2022 7 citations

2023 28 citations

2024 10 citations

2025 8 citations

2026 0 citations

S. Ridella

PROFILE

PAPERS

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