Merra, Felice Antonio
 Distribuzione geografica
Continente #
EU - Europa 518
NA - Nord America 486
AS - Asia 135
OC - Oceania 2
SA - Sud America 1
Totale 1.142
Nazione #
US - Stati Uniti d'America 477
IE - Irlanda 147
IT - Italia 118
SE - Svezia 46
BG - Bulgaria 44
HK - Hong Kong 44
DE - Germania 42
FI - Finlandia 33
PL - Polonia 29
NL - Olanda 26
SG - Singapore 26
CN - Cina 25
VN - Vietnam 18
MY - Malesia 13
UA - Ucraina 11
CA - Canada 8
ES - Italia 7
RU - Federazione Russa 5
FR - Francia 4
GB - Regno Unito 3
AU - Australia 2
IL - Israele 2
AE - Emirati Arabi Uniti 1
AM - Armenia 1
AR - Argentina 1
BD - Bangladesh 1
BE - Belgio 1
DK - Danimarca 1
GE - Georgia 1
JM - Giamaica 1
KG - Kirghizistan 1
LK - Sri Lanka 1
PH - Filippine 1
SK - Slovacchia (Repubblica Slovacca) 1
Totale 1.142
Città #
Dublin 145
Chandler 83
New York 59
Sofia 44
Hong Kong 43
Bari 32
Boardman 31
Helsinki 31
Jacksonville 29
Warsaw 28
Malden 24
Santa Clara 24
Singapore 23
Ashburn 18
Bremen 18
Ogden 16
Dong Ket 14
San Mateo 14
Brielle 12
Lawrence 12
Wilmington 9
Altamura 8
Amsterdam 6
Brooklyn 6
Chicago 6
Madrid 6
Poggibonsi 6
Miami 5
Shanghai 5
Toronto 5
Cagliari 4
Dronten 4
Hanoi 4
San Francisco 4
Frankfurt am Main 3
Guangzhou 3
Locorotondo 3
Meppel 3
Messina 3
Rome 3
Treviso 3
Berlin 2
Colle 2
Hanover 2
Lappeenranta 2
Noicattaro 2
Ottawa 2
Seattle 2
Shenzhen 2
Washington 2
Adelaide 1
Atlanta 1
Bishkek 1
Bratislava 1
Brindisi 1
Burlington 1
Cebu City 1
Changsha 1
Charleston 1
Colombo 1
Des Moines 1
Dhaka 1
Fairfield 1
Falkenstein 1
Halle 1
Hangzhou 1
Jinhua 1
Laterza 1
Le Havre 1
Los Angeles 1
Melbourne 1
Milan 1
Molfetta 1
Nanjing 1
Nuremberg 1
Palermo 1
Pontirolo Nuovo 1
Portland 1
Potenza 1
Redmond 1
Río Cuarto 1
San Severo 1
Tbilisi 1
Trani 1
Vedelago 1
Visciano 1
Wuhan 1
Yerevan 1
Yurovka 1
Totale 856
Nome #
Adversarial Machine Learning in Recommender Systems 158
Assessing the impact of a user-item collaborative attack on class of users 95
A Survey on Adversarial Recommender Systems: From Attack/Defense Strategies to Generative Adversarial Networks 75
Adversarial machine learning in recommender systems (AML-RECSYS) 69
TAaMR: Targeted Adversarial Attack against Multimedia Recommender Systems 67
Assessing perceptual and recommendation mutation of adversarially-poisoned visual recommenders 63
How Dataset Characteristics Affect the Robustness of Collaborative Recommendation Models 63
SAShA: Semantic-Aware Shilling Attacks on Recommender Systems Exploiting Knowledge Graphs 60
Adversarial Learning for Recommendation: Applications for Security and Generative Tasks — Concept to Code 60
A Study of Defensive Methods to Protect Visual Recommendation against Adversarial Manipulation of Images 60
Knowledge-enhanced Shilling Attacks for Recommendation 54
Elliot: A Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation 52
A Formal Analysis of Recommendation Quality of Adversarially-trained Recommenders 41
A regression framework to interpret the robustness of recommender systems against shilling attacks 38
Denoise to Protect: A Method to Robustify Visual Recommenders from Adversaries 38
Leveraging Content-Style Item Representation for Visual Recommendation 37
A Study on the Relative Importance of Convolutional Neural Networks in Visually-Aware Recommender Systems 36
Adversarial Recommender Systems: Attack, Defense, and Advances 30
MSAP: Multi-Step Adversarial Perturbations on Recommender Systems Embeddings 30
V-Elliot: Design, evaluate and tune visual recommender systems 15
The Challenging Reproducibility Task in Recommender Systems Research between Traditional and Deep Learning Models 14
How to perform reproducible experiments in the ELLIOT recommendation framework: Data processing, model selection, and performance evaluation 14
Formalizing Multimedia Recommendation through Multimodal Deep Learning 5
Totale 1.174
Categoria #
all - tutte 6.591
article - articoli 0
book - libri 0
conference - conferenze 0
curatela - curatele 0
other - altro 0
patent - brevetti 0
selected - selezionate 0
volume - volumi 0
Totale 6.591


Totale Lug Ago Sett Ott Nov Dic Gen Feb Mar Apr Mag Giu
2019/20207 0 0 0 0 0 0 0 0 0 0 5 2
2020/202198 4 2 6 10 4 6 12 13 5 13 0 23
2021/2022298 5 4 7 31 19 22 21 10 32 72 19 56
2022/2023405 26 1 17 18 52 28 0 27 189 31 11 5
2023/2024260 20 10 6 11 62 71 2 11 21 5 1 40
2024/2025106 10 4 54 2 27 9 0 0 0 0 0 0
Totale 1.174