Address

    Contact Information

    Phone: +39 080 5963641

    Email: yashar.deldjoo@poliba.it


    Teaching

    Distributed Systems

    Yashar Deldjoo

    Associate Professor

    Publications

    Adversarial Attacks Against Visually Aware Fashion Outfit Recommender Systems
    Workshop on Recommender Systems in Fashion and Retail (RecSys 2022)

    DOI: 10.1007/978-3-031-22192-7_4

    Auditing Consumer-and Producer-Fairness in Graph Collaborative Filtering
    Advances in Information Retrieval 45th European Conference on Information Retrieval

    DOI: 10.1007/978-3-031-28244-7_3

    Reshaping Graph Recommendation with Edge Graph Collaborative Filtering and Customer Reviews
    Workshop Deep Learning for Search and Recommendation

    DOI: 10.1145/3460231.3475944

    How Neighborhood Exploration influences Novelty and Diversity in Graph Collaborative Filtering
    MORS 2022: The Second Workshop on Multi-Objective Recommender Systems

    DOI: 10.1145/3460231.3475944

    A Study of Defensive Methods to Protect Visual Recommendation Against Adversarial Manipulation of Images
    Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval

    DOI: 10.1145/3404835.3462848

    A Study on the Relative Importance of Convolutional Neural Networks in Visually-Aware Recommender Systems
    Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops

    DOI: 10.1109/cvprw53098.2021.00445

    User-Controlled Federated Matrix Factorization for Recommender Systems
    Journal of Intelligent Information Systems

    DOI: 10.1007/s10844-021-00688-z

    Leveraging Content-Style Item Representation for Visual Recommendation
    44th European Conference on Information Retrieval

    DOI:

    Federated Recommender Systems with Learning to Rank
    SEBD 2021: The 29th Italian Symposium on Advanced Database Systems

    DOI: 10.1145/3460231.3478858

    Pursuing Privacy in Recommender Systems: the View of Users and Researchers from Regulations to Applications
    RecSys 21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 2021

    DOI: 10.1145/3460231.3473326

    Adversarial Recommender Systems: Attack, Defense, and Advances

    DOI: 10.1145/3357384.3358805

    Adversarial Learning for Recommendation
    Adversarial Machine Learning, Recommender SystemsAdvances in Information Retrieval -43rd European Conference on {IR} Research, {ECIR} 2021

    DOI: 10.1145/3383313.3411447

    FedeRank: User Controlled Feedback with Federated Recommender Systems
    Advances in Information Retrieval - ECIR 2021, 43rd European Conference on IR Research

    DOI: 10.1007/s11257-020-09285-1

    How to Put Users in Control of their Data in Federated Top-N Recommendation with Learning to Rank
    Proceedings of the 36th ACM SIGAPP Symposium On Applied Computing, SAC 2021, Gwangju, Korea (Virtual Event)

    DOI: 10.3233/ia-200054

    Adversarial Learning for Recommendation: Applications for Security and Generative Tasks - Concept to Code
    The 14th ACM Conference on Recommender Systems, September 21--26, 2020, Virtual Event, Brazil

    DOI: 10.1145/3383313.3411447

    Recommender Systems Leveraging Multimedia Content
    content-based recommender systems, multimedia, machine learning, deep learning, signal processing, audio, music, image, video, fashion, food, e-commerce, tourism, social mediaACM Computing Surveys

    DOI: 10.1109/cbmi.2019.8877452

    Prioritized Multi-Criteria Federated Learning
    Intelligenza Artificiale

    DOI: 10.3233/ia-200054

    Deep Learning-Based Adaptive Image Compression System for a Real-World Scenario
    Proceedings of the IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2020)

    DOI: 10.1109/eais48028.2020.9122753

    Knowledge-enhanced Shilling Attacks for recommendation
    Shilling Attack, Recommender SystemThe 28th Italian Symposium on Advanced Database Systems (SEBD 2020), Villasimius (CA), Italy, June 21-24, 2020

    DOI: 10.1007/978-3-030-49461-2_18

    A survey on Adversarial Recommender Systems: from Attack/Defense strategies to Generative Adversarial Networks
    Recommender System, Adversarial Machine Learning, Literature ReviewACM Computing Surveys

    DOI: 10.1145/3439729

    How Dataset Characteristics Affect the Robustness of Collaborative Recommendation Models
    Proc. of ACM SIGIR 2020 - 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval

    DOI: 10.1145/3397271.3401046

    Adversarial Machine Learning in Recommender Systems (AML-RecSys)
    WSDM'20: The Thirteenth ACM International Conference on Web Search and Data Mining, Houston, TX, USA, February 3-7, 2020

    DOI: 10.1145/3336191.3371877

    SAShA: Semantic-Aware Shilling Attacks on Recommender Systems exploiting Knowledge Graphs
    17th European Semantic Web Conference ESWC 2020

    DOI: 10.1007/978-3-030-49461-2_18

    Towards Effective Device-Aware Federated Learning
    federated learning; aggregation; data distributionIn Proceedings of the 18th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2019)

    DOI: 10.1007/978-3-030-35166-3_34

    Recommender Systems Fairness Evaluation via Generalized Cross Entropy
    Recommender systems; fairness; metric; Generalized cross entropy;evaluationIn Proceedings of the 13th ACM RecSys Workshop on Recommendation in Multistakeholder Environments (RMSE@RecSys'19)

    DOI: 10.1145/3240323.3241620

    Assessing the Impact of a User-Item Collaborative Attack on Class of Users
    shilling attack: recommender systems; user classIn Proceedings of the 13th ACM RecSys Workshop on Impact of Recommender Systems, (ImpactRS@RecSys'19)

    DOI: 10.1007/s11257-020-09285-1