IRIS
RIDELLA, SANDRO
 Distribuzione geografica
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Continente #
EU - Europa 11.161
Totale 11.161
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Nazione #
IT - Italia 11.161
Totale 11.161
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Città #
Genova 8.635
Rapallo 1.124
Genoa 857
Vado Ligure 524
Bordighera 21
Totale 11.161
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Nome #
Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels 164
Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates 140
Representation and generalization properties of class-entropy networks 138
A support vector machine with integer parameters 137
CBP networks as a generalized neural model 135
Theoretical and Practical Model Selection Methods for Support Vector Classifiers 135
A Novel Procedure for Training L1-L2 Support Vector Machine Classifiers 135
K-Winner Machines for pattern classification 135
Block Distortion Assessment for Image Compression Through ANNs 133
Automatic Hyperparameter Tuning for Support Vector Machines 132
K-Fold Generalization Capability Assessment for Support Vector Classifiers 132
A New Method for Multiclass Support Vector Machines 131
Distributed key-generation structures for associative image-classification. 130
Selecting the hypothesis space for improving the generalization ability of support vector machines 128
Characterization of a cellular Array of Dipoles for Molecular Information Processing 125
Using Unsupervised Analysis to Constrain Generalization Bounds for Support Vector Classifiers 125
A FPGA Core Generator for Embedded Classification Systems 125
Unlabeled Patterns to Tighten Rademacher Complexity Error Bounds for Kernel Classifiers 124
A VLSI friendly algorithm for support vector machines 124
Tikhonov, Ivanov and Morozov regularization for support vector machine learning 124
Some considerations about the frequency dependence of the characteristic impedance of uniform microstrips 123
Fast convergence of extended Rademacher Complexity bounds 122
Vector Quantization Complexity and Quantum Computing 121
In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines 121
Performance characterization of K-Winner Machines 119
An Improved Analysis of the Rademacher Data-dependent Bound Using Its Self-Bounding Property 119
Maximal Discrepancy for Support Vector Machines 117
A Hardware-friendly Support Vector Machine for Embedded Automotive Applications 117
Circular backpropagation networks embed vector quantization 115
Maximal Discrepancy for Support Vector Machines 115
Augmenting vector quantization with interval arithmetics for image-coding applications 115
Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency 114
Circuital implementation of support vector machines 113
A model-selection approach to the VLSI design of vector quantizers 113
Computation of the scattering matrix of a class of reciprocal lossless 2-ports from one short-circuit measurement 112
Learning Algorithm for Nonlinear Support Vector Machines Suited for Digital VLSI 112
Training support vector machines: a quantum-computing perspective. 112
Support vector machines and strictly positive definite kernel: The regularization hyperparameter is more important than the kernel hyperparameters 112
A digital architecture for support vector machines: theory, algorithm and FPGA implementation 110
Hyperparameter design criteria for support vector classifiers 110
A Support Vector Machine Classifier from a Bit-Constrained, Sparse and Localized Hypothesis Space 110
Learning the mean: A neural network approach 110
Some Results About the Vapnik-Chervonenkis Entropy and the Rademacher Complexity 109
Learning Hardware-Friendly Classifiers through Algorithmic Stability 109
Incorporating a-priori knowledge into neural networks 109
Using chaos to generate keys for associative noise-like coding memories 106
The k-winner machine model 106
Feed-forward Support Vector Machine without Multipliers 104
Digital implementation of Hierarchical Vector Quantization 104
A local Vapnik-Chervonenkis complexity 104
Model Selection for Support Vector Machines: Advantages and Disadvantages of the Machine Learning Theory 104
Worst case analysis of weight inaccuracy effects in multilayer perceptrons 104
Randomized learning: Generalization performance of old and new theoretically grounded algorithms 104
Using K-Winner Machines for domain analysis 103
In-Sample Model Selection for Trimmed Hinge Loss Support Vector Machine 103
Circular back-propagation networks for classification 102
Adaptive representation properties of the circular back-propgation model 101
Rademacher Complexity and Structural Risk Minimization: an Application to Human Gene Expression Datasets 101
The ‘K’ in K-fold Cross Validation 99
Local Rademacher Complexity: Sharper risk bounds with and without unlabeled samples 99
Differential privacy and generalization: Sharper bounds with applications 99
Test Error Bounds for Classifiers: A Survey of Old and New Results 98
Adaptive internal representation in circular back-propagation networks 97
Open-circuited coaxial lines as standards for microwave measurements 97
Quantum optimization for training support vector machines 96
Model Selection in Top Quark Tagging with a Support Vector Classifier 96
Using Variable Neighborhood Search to Improve the Support Vector Machine Performance in Embedded Automotive Applications 94
Generalization-based approach to plastic vector quantization 93
A deep connection between the vapnik-chervonenkis entropy and the rademacher complexity 93
PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis 93
Prospects of quantum-classical optimization for digital design 93
Circuit implementation of the k-winner machine 92
A Learning Machine with a Bit-Based Hypothesis Space 92
Pruning and rule extraction using class entropy 92
Testing the Augmented Binary Multiclass SVM on Microarray Data 92
On the importance of sorting in “Neural Gas” for training vector quantizers 91
Comments on Microstrip Characteristic Impedance 90
Electrical modeling of cells 90
Smartphone battery saving by bit-based hypothesis spaces and local Rademacher Complexities 90
Plastic algorithm for adaptive vector quantization 88
Out-of-Sample Error Estimation: The Blessing of High Dimensionality 88
Fully Empirical and Data-Dependent Stability-Based Bounds 88
In-sample Model Selection for Support Vector Machines 87
Empirical Measure of Multiclass Generalization Performance: the K-Winner Machine Case 86
On the design of a travelling wave-thin film amplifier 86
K–Fold Cross Validation for Error Rate Estimate in Support Vector Machines 85
A circuit model for terminated microstrips 85
Learning the appropriate representation paradigm by circular processing units 81
Evaluating the Generalization Ability of Support Vector Machines through the Bootstrap 81
Unsupervised Clustering and the Capacity of Support Vector Machines 81
Shrinkage learning to improve SVM with hints 81
Quantum computing and supervised machine learning: Training, model selection, and error estimation 80
Local Rademacher Complexity Machine 79
Impatt diode modelling and identification 78
Class-entropy minimization networks for domain analysis and rule extraction 74
Nested Sequential Minimal Optimization for Support Vector Machine 73
Identification of a classs of two-port networks from one short-circuit measurement 70
Launcher's and microstrip characterization 66
Non-interacting Ellipsoidal Body Suspensions 66
Representation plasticity in classifier networks with circular activation units 65
Totale 10.501
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Categoria #
all - tutte 31.617
article - articoli 15.948
book - libri 0
conference - conferenze 14.131
curatela - curatele 0
other - altro 0
patent - brevetti 353
selected - selezionate 0
volume - volumi 1.185
Totale 63.234
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Totale Lug Ago Sett Ott Nov Dic Gen Feb Mar Apr Mag Giu
2019/20202.558 0 0 0 0 271 318 465 194 290 521 331 168
2020/2021800 72 111 89 48 41 88 21 72 65 83 52 58
2021/20221.395 26 100 113 168 31 93 88 329 68 127 82 170
2022/20231.363 131 87 7 158 210 244 14 84 213 4 188 23
2023/2024633 32 101 19 57 28 118 49 33 30 16 46 104
2024/2025545 44 185 50 99 167 0 0 0 0 0 0 0
Totale 11.325