IRIS
RIDELLA, SANDRO
 Distribuzione geografica
Salva come PNG Salva come JPEG
Continente #
EU - Europa 13.643
AS - Asia 1.341
NA - Nord America 1.000
Continente sconosciuto - Info sul continente non disponibili 179
SA - Sud America 112
AF - Africa 21
Totale 16.296
Salva come PNG Salva come JPEG
Nazione #
IT - Italia 13.427
US - Stati Uniti d'America 921
SG - Singapore 559
CN - Cina 390
VN - Vietnam 188
FR - Francia 112
BD - Bangladesh 72
BR - Brasile 68
HK - Hong Kong 39
MX - Messico 24
CA - Canada 22
DE - Germania 20
AR - Argentina 19
GB - Regno Unito 19
IN - India 19
JP - Giappone 14
FI - Finlandia 10
NL - Olanda 10
JM - Giamaica 8
ES - Italia 7
HN - Honduras 7
CH - Svizzera 6
CO - Colombia 6
ID - Indonesia 6
IQ - Iraq 6
PH - Filippine 6
PK - Pakistan 6
RU - Federazione Russa 6
TH - Thailandia 6
TR - Turchia 6
CR - Costa Rica 5
VE - Venezuela 5
EC - Ecuador 4
IE - Irlanda 4
NP - Nepal 4
PE - Perù 4
PL - Polonia 4
MA - Marocco 3
MY - Malesia 3
PY - Paraguay 3
SA - Arabia Saudita 3
SE - Svezia 3
TN - Tunisia 3
TW - Taiwan 3
UA - Ucraina 3
ZA - Sudafrica 3
EE - Estonia 2
EG - Egitto 2
GT - Guatemala 2
JO - Giordania 2
LB - Libano 2
LT - Lituania 2
NG - Nigeria 2
OM - Oman 2
PR - Porto Rico 2
PT - Portogallo 2
TT - Trinidad e Tobago 2
AL - Albania 1
AO - Angola 1
AZ - Azerbaigian 1
BG - Bulgaria 1
BO - Bolivia 1
BS - Bahamas 1
CI - Costa d'Avorio 1
CL - Cile 1
DJ - Gibuti 1
DO - Repubblica Dominicana 1
DZ - Algeria 1
GA - Gabon 1
GD - Grenada 1
HR - Croazia 1
HU - Ungheria 1
IR - Iran 1
LC - Santa Lucia 1
LK - Sri Lanka 1
MU - Mauritius 1
NI - Nicaragua 1
PA - Panama 1
QA - Qatar 1
RO - Romania 1
SC - Seychelles 1
SK - Slovacchia (Repubblica Slovacca) 1
SN - Senegal 1
SV - El Salvador 1
UY - Uruguay 1
UZ - Uzbekistan 1
Totale 16.117
Salva come PNG Salva come JPEG
Città #
Genova 8.635
Genoa 2.725
Rapallo 1.124
Vado Ligure 825
Singapore 266
San Jose 251
Lauterbourg 105
Beijing 68
Ashburn 60
Ho Chi Minh City 58
New York 49
Hanoi 46
Santa Clara 42
Hong Kong 36
Bordighera 21
Frankfurt am Main 17
Mexico City 17
Atlanta 13
Los Angeles 13
Tokyo 13
Orem 11
Chicago 10
Dallas 10
Helsinki 10
Poplar 10
Milan 9
Boardman 8
Buffalo 8
Council Bluffs 8
Haiphong 8
Amsterdam 7
Da Nang 6
Houston 6
Naples 6
Tianjin 6
Zurich 6
Bangkok 5
Charlotte 5
Denver 5
Des Moines 5
Queens 5
Rome 5
Turin 5
Columbia 4
Florence 4
Kingston 4
Mumbai 4
São Paulo 4
Toronto 4
Wilmington 4
Alexandria 3
Bari 3
Biên Hòa 3
Brooklyn 3
Bắc Ninh 3
Canton 3
City of London 3
Covington 3
Curitiba 3
Dhaka 3
Dublin 3
Fayetteville 3
Lima 3
London 3
Montreal 3
Nanjing 3
Nashville 3
New Delhi 3
Oakland 3
Orlando 3
Philadelphia 3
Phoenix 3
Quincy 3
Seattle 3
Tegucigalpa 3
The Bronx 3
Tunis 3
Warsaw 3
Amman 2
Asunción 2
Baghdad 2
Baldwin Park 2
Baltimore 2
Bellingham 2
Billings 2
Bologna 2
Brent 2
Chengdu 2
Chennai 2
Chula Vista 2
Cicero 2
Cincinnati 2
Dayton 2
Detroit 2
East Brunswick 2
El Dorado Hills 2
Elgin 2
Endicott 2
Everett 2
Guangzhou 2
Totale 14.704
Salva come PNG Salva come JPEG
Nome #
Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels 210
A local Vapnik-Chervonenkis complexity 201
A Novel Procedure for Training L1-L2 Support Vector Machine Classifiers 200
A support vector machine with integer parameters 199
Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates 193
A New Method for Multiclass Support Vector Machines 188
A FPGA Core Generator for Embedded Classification Systems 187
A Hardware-friendly Support Vector Machine for Embedded Automotive Applications 183
K-Fold Generalization Capability Assessment for Support Vector Classifiers 183
Fast convergence of extended Rademacher Complexity bounds 182
A Support Vector Machine Classifier from a Bit-Constrained, Sparse and Localized Hypothesis Space 181
CBP networks as a generalized neural model 180
K-Winner Machines for pattern classification 180
Characterization of a cellular Array of Dipoles for Molecular Information Processing 179
Theoretical and Practical Model Selection Methods for Support Vector Classifiers 179
Automatic Hyperparameter Tuning for Support Vector Machines 178
Representation and generalization properties of class-entropy networks 177
Block Distortion Assessment for Image Compression Through ANNs 177
An Improved Analysis of the Rademacher Data-dependent Bound Using Its Self-Bounding Property 177
A model-selection approach to the VLSI design of vector quantizers 175
A VLSI friendly algorithm for support vector machines 173
Using Unsupervised Analysis to Constrain Generalization Bounds for Support Vector Classifiers 172
A digital architecture for support vector machines: theory, algorithm and FPGA implementation 168
Computation of the scattering matrix of a class of reciprocal lossless 2-ports from one short-circuit measurement 165
Tikhonov, Ivanov and Morozov regularization for support vector machine learning 164
Augmenting vector quantization with interval arithmetics for image-coding applications 164
Distributed key-generation structures for associative image-classification. 163
Randomized learning: Generalization performance of old and new theoretically grounded algorithms 163
In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines 161
Adaptive representation properties of the circular back-propgation model 158
Unlabeled Patterns to Tighten Rademacher Complexity Error Bounds for Kernel Classifiers 158
A deep connection between the vapnik-chervonenkis entropy and the rademacher complexity 157
Selecting the hypothesis space for improving the generalization ability of support vector machines 156
A Learning Machine with a Bit-Based Hypothesis Space 155
Circuital implementation of support vector machines 153
Maximal Discrepancy for Support Vector Machines 153
The k-winner machine model 151
Some considerations about the frequency dependence of the characteristic impedance of uniform microstrips 151
Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency 151
Support vector machines and strictly positive definite kernel: The regularization hyperparameter is more important than the kernel hyperparameters 149
Performance characterization of K-Winner Machines 148
Vector Quantization Complexity and Quantum Computing 147
On the importance of sorting in “Neural Gas” for training vector quantizers 147
Circular backpropagation networks embed vector quantization 145
A circuit model for terminated microstrips 145
Maximal Discrepancy for Support Vector Machines 145
Differential privacy and generalization: Sharper bounds with applications 145
Impatt diode modelling and identification 144
Training support vector machines: a quantum-computing perspective. 144
Local Rademacher Complexity: Sharper risk bounds with and without unlabeled samples 144
Incorporating a-priori knowledge into neural networks 144
Using chaos to generate keys for associative noise-like coding memories 143
Adaptive internal representation in circular back-propagation networks 143
Circular back-propagation networks for classification 142
The ‘K’ in K-fold Cross Validation 142
Learning the mean: A neural network approach 142
In-Sample Model Selection for Trimmed Hinge Loss Support Vector Machine 142
Learning Hardware-Friendly Classifiers through Algorithmic Stability 141
Learning Algorithm for Nonlinear Support Vector Machines Suited for Digital VLSI 140
Worst case analysis of weight inaccuracy effects in multilayer perceptrons 139
Hyperparameter design criteria for support vector classifiers 138
Some Results About the Vapnik-Chervonenkis Entropy and the Rademacher Complexity 138
Rademacher Complexity and Structural Risk Minimization: an Application to Human Gene Expression Datasets 138
Model Selection for Support Vector Machines: Advantages and Disadvantages of the Machine Learning Theory 138
Comments on Microstrip Characteristic Impedance 135
Feed-forward Support Vector Machine without Multipliers 134
Fully Empirical and Data-Dependent Stability-Based Bounds 134
Unsupervised Clustering and the Capacity of Support Vector Machines 133
Identification of a classs of two-port networks from one short-circuit measurement 132
Digital implementation of Hierarchical Vector Quantization 131
Electrical modeling of cells 129
Prospects of quantum-classical optimization for digital design 129
Open-circuited coaxial lines as standards for microwave measurements 128
Model Selection in Top Quark Tagging with a Support Vector Classifier 128
Class-entropy minimization networks for domain analysis and rule extraction 127
Test Error Bounds for Classifiers: A Survey of Old and New Results 127
Generalization-based approach to plastic vector quantization 126
Using K-Winner Machines for domain analysis 126
Using Variable Neighborhood Search to Improve the Support Vector Machine Performance in Embedded Automotive Applications 125
Testing the Augmented Binary Multiclass SVM on Microarray Data 125
PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis 124
Quantum optimization for training support vector machines 122
Plastic algorithm for adaptive vector quantization 122
K–Fold Cross Validation for Error Rate Estimate in Support Vector Machines 122
Smartphone battery saving by bit-based hypothesis spaces and local Rademacher Complexities 121
In-sample Model Selection for Support Vector Machines 121
Pruning and rule extraction using class entropy 120
Quantum computing and supervised machine learning: Training, model selection, and error estimation 119
Circuit implementation of the k-winner machine 118
On the design of a travelling wave-thin film amplifier 118
Evaluating the Generalization Ability of Support Vector Machines through the Bootstrap 117
Local Rademacher Complexity Machine 117
Shrinkage learning to improve SVM with hints 113
Empirical Measure of Multiclass Generalization Performance: the K-Winner Machine Case 112
The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers. 112
Out-of-Sample Error Estimation: The Blessing of High Dimensionality 112
Quantum-computing optimization for K-Winner Machines 110
Learning the appropriate representation paradigm by circular processing units 108
Structural Risk Minimization and Rademacher Complexity for Regression 103
Nested Sequential Minimal Optimization for Support Vector Machine 101
Totale 14.699
Salva come PNG Salva come JPEG
Categoria #
all - tutte 49.788
article - articoli 24.823
book - libri 0
conference - conferenze 22.476
curatela - curatele 0
other - altro 0
patent - brevetti 634
selected - selezionate 0
volume - volumi 1.855
Totale 99.576
Salva come PNG Salva come JPEG


Totale Lug Ago Sett Ott Nov Dic Gen Feb Mar Apr Mag Giu
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
2024/20251.821 44 185 50 99 308 194 191 239 58 66 163 224
2025/20263.321 346 91 221 316 410 386 563 120 247 288 116 217
2026/2027374 374 0 0 0 0 0 0 0 0 0 0 0
Totale 16.296