Address

    Contact Information

    Phone: +39 080 5963641

    Email: yashar.deldjoo@poliba.it


    Teaching

    Distributed Systems

    Yashar Deldjoo

    Assistant Professor

    Publications

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

    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)

    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

    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

    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

    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

    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)

    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)

    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)