Repositories
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Visual-Adversarial-Recommendation
we present an evaluation framework, named Visual Adversarial Recommender (\var), to empirically investigate the performance of defended or undefended DNNs in various visually-aware item recommendation tasks.
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MSAP
In this work, we extend the FGSM method proposing multistep adversarial perturbation (MSAP) procedures to study the recommenders’ robustness under powerful methods. Letting fixed the perturbation magnitude, we illustrate that MSAP is much more harmful than FGSM in corrupting the recommendation performance of BPR-MF.
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elliot
Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
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iir2021
IIR 2021 | 11th Italian Information Retrieval Workshop
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CNNs-in-VRSs
Accepted at CVFAD@CVPR 2021
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Image-Feature-Extractor
A Python implementation to extract visual features from images through pretrained CNNs.
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amlrecsys-tutorial
Tutorial by Yashar Deldjoo, Tommaso Di Noia and Felice Antonio Merra at WSDM 2020 about Adversarial Machine Learning in Recommender Systems
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TAaMR
Targeted Adversarial Attack against Multimedia Recommender Systems (TAaMR) at DSML2020
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adversarial-recommender-systems-survey
The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show another successful application of AML in generative adversarial networks (GANs) for generative applications, thanks to their ability for learning (high-…
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SAShA-against-CFRS
Semantics-Aware Shilling Attacks against collaborative recommender systems via Knowledge Graphs
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interactive-question-answering-systems-survey
A collection of work regarding Interactive Question Answering System standing over 10 years.
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helpdesk
home page for sisinflab helpdesk
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Perceptual-Rec-Mutation-of-Adv-VRs
Accepted at WDSC@NeurIPS2020
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papers-results
Papers Results
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poldo
A tool for exposing the deep Web in the Linked Data cloud
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SEMAUTO-2.0
Semantics-Aware Autoencoder Neural Network
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Musica-Humana
Progetto sviluppato in collaborazione fra Politecnico di Bari e Conservatorio di Matera
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DatasetsSplits
This is a collection of splittings of publicly available Datasets. This collection has been created for two main purposes:
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anna
Vocal Assistant / Chatbot Anna to explore Puglia Digital Library
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The-importance-of-being-dissimilar-in-Recommendation
Similarity measures play a fundamental role in memory-based nearest neighbors approaches. They recommend items to a user based on the similarity of either items or users in a neighborhood. In this paper we argue that, although it keeps a leading importance in computing recommendations, similarity between users or items should be paired with a va…
