Address

    Contact Information


    Teaching

    Algoritmi e Strutture Dati in Java

    Daniele Malitesta

    Postdoc Researcher @CentraleSupélec
    PhD Graduated 2024 @SisInfLab

    Publications

    A Novel Evaluation Perspective on GNNs-based Recommender Systems through the Topology of the User-Item Graph
    Proceedings of the 18th ACM Conference on Recommender Systems (RecSys 2024)

    DOI: 10.1145/3640457.3688070

    Denoise to Protect: A Method to Robustify Visual Recommenders from Adversaries
    Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023)

    DOI: 10.1145/3539618.3591971

    DataRec: A Python Library for Standardized and Reproducible Data Management in Recommender Systems
    The 48th International ACM SIGIR Conference on Research and Development in Information Retrieval

    DOI:

    KGUF: Simple Knowledge-Aware Graph-Based Recommender with User-Based Semantic Features Filtering
    Advances on Graph-Based Approaches in Information Retrieval

    DOI: 10.1007/978-3-031-71382-8_4

    Ducho 2.0: Towards a More Up-to-Date Feature Extraction and Processing Framework for Multimodal Recommendation
    Proceedings of the ACM Web Conference 2024

    DOI: 10.1145/3589335.3651440

    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

    KGTORe: Tailored Recommendations through Knowledge-aware GNN Models
    Proceedings of the 17th ACM Conference on Recommender Systems

    DOI: 10.1145/3604915.3608804

    Ducho: A Unified Framework for the Extraction of Multimodal Features in Recommendation
    The 31st ACM International Conference on Multimedia

    DOI: 10.1007/978-3-030-99739-7_10

    Disentangling the Performance Puzzle of Multimodal-aware Recommender Systems
    The 2nd Edition of EvalRS: a Rounded Evzaluation of Recommender Systems (KDD 2023)

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

    An Out-of-the-Box Application for Reproducible Graph Collaborative Filtering extending the Elliot Framework
    Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization

    DOI: 10.1145/3563359.3597411

    Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis
    The 17th ACM Conference on Recommender Systems

    DOI: 10.1145/3563359.3597411

    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

    V-Elliot: Speeding up Visual Recommendation via a GPU-powered Data Input Pipeline
    NVIDIA GTC 2022

    DOI:

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

    DOI:

    V-Elliot: Design, Evaluate and Tune Visual Recommender Systems
    RecSys 21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 2021

    DOI: 10.1145/3460231.3478881

    How to Perform Reproducible Experiments in the ELLIOT Recommendation Framework: Data Processing, Model Selection, and Performance Evaluation
    11th Italian Information Retrieval Workshop 2021, Bari, Italy, 2021

    DOI: ceur-ws.org/Vol-2947/

    Elliot: A Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
    The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, 2021

    DOI: 10.1145/3404835.3463245

    Assessing Perceptual and Recommendation Mutation of Adversarially-Poisoned Visual Recommenders
    Adversarial Machine Learning, Recommender Systems, Deep LearningThe 1st Workshop on Dataset Curation and Security co-located with the 34th Conference on Neural InformationProcessing Systems (NeurIPS 2020), Vancouver, Canada (Virtual Event).

    DOI: 10.1145/3125486.3125496

    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

    TAaMR: Targeted Adversarial Attack against Multimedia Recommender Systems
    Adversarial Machine Learning, Recommender SystemsThe 3rd International Workshop on Dependable and Secure Machine Learning – DSML 2020 Co-located with the 50th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2020)

    DOI: 10.1109/dsn-w50199.2020.00011