Search Results - Pomo, Claudio

Refine Results
  1. 1
    Auditing fairness under unawareness through counterfactual reasoning

    Auditing fairness under unawareness through counterfactual reasoning by Cornacchia, Giandomenico, Anelli, Vito Walter, Biancofiore, Giovanni Maria, Narducci, Fedelucio, Pomo, Claudio, Ragone, Azzurra, Di Sciascio, Eugenio

    Get full text
    Items that this one cites
    Items that cite this one
    Article
    Save to List
    Saved in:
  2. 2
    Conversational recommendation: Theoretical model and complexity analysis

    Conversational recommendation: Theoretical model and complexity analysis by Di Noia, Tommaso, Donini, Francesco Maria, Jannach, Dietmar, Narducci, Fedelucio, Pomo, Claudio

    Published in Information sciences
    Get full text
    Items that this one cites
    Items that cite this one
    Article
    Save to List
    Saved in:
  3. 3
    A qualitative analysis of knowledge graphs in recommendation scenarios through semantics-aware autoencoders

    A qualitative analysis of knowledge graphs in recommendation scenarios through semantics-aware autoencoders by Bellini, Vito, Di Sciascio, Eugenio, Donini, Francesco Maria, Pomo, Claudio, Ragone, Azzurra, Schiavone, Angelo

    Get full text
    Items that this one cites
    Article
    Save to List
    Saved in:
  4. 4
    Formalizing Multimedia Recommendation through Multimodal Deep Learning

    Formalizing Multimedia Recommendation through Multimodal Deep Learning by Malitesta, Daniele, Cornacchia, Giandomenico, Pomo, Claudio, Merra, Felice Antonio, Di Noia, Tommaso, Di Sciascio, Eugenio

    Get full text
    Items that this one cites
    Article
    Save to List
    Saved in:
  5. 5
    On fast prototyping LoRaWAN: a cheap and open platform for daily experiments

    On fast prototyping LoRaWAN: a cheap and open platform for daily experiments by Pulpito, Mariano, Fornarelli, Paolo, Pomo, Claudio, Boccadoro, Pietro, Grieco, Luigi Alfredo

    Request full text
    Items that this one cites
    Items that cite this one
    Article
    Save to List
    Saved in:
  6. 6
    Graph Neural Networks for Recommendation: Reproducibility, Graph Topology, and Node Representation

    Graph Neural Networks for Recommendation: Reproducibility, Graph Topology, and Node Representation by Malitesta, Daniele, Pomo, Claudio, Tommaso Di Noia

    Published in arXiv.org
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    EB-NeRD: A Large-Scale Dataset for News Recommendation

    EB-NeRD: A Large-Scale Dataset for News Recommendation by Kruse, Johannes, Kasper Lindskow, Kalloori, Saikishore, Polignano, Marco, Pomo, Claudio, Srivastava, Abhishek, Uppal, Anshuk, Andersen, Michael Riis, Frellsen, Jes

    Published in arXiv.org
    Get full text
    Article
    Save to List
    Saved in:
  8. 8
    RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations

    RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations by Kruse, Johannes, Kasper Lindskow, Kalloori, Saikishore, Polignano, Marco, Pomo, Claudio, Srivastava, Abhishek, Uppal, Anshuk, Andersen, Michael Riis, Frellsen, Jes

    Published in arXiv.org
    Get full text
    Article
    Save to List
    Saved in:
  9. 9
    Formalizing Multimedia Recommendation through Multimodal Deep Learning

    Formalizing Multimedia Recommendation through Multimodal Deep Learning by Malitesta, Daniele, Cornacchia, Giandomenico, Pomo, Claudio, Merra, Felice Antonio, Tommaso Di Noia, Eugenio Di Sciascio

    Published in arXiv.org
    Get full text
    Article
    Save to List
    Saved in:
  10. 10
    Fashion Image-to-Image Translation for Complementary Item Retrieval

    Fashion Image-to-Image Translation for Complementary Item Retrieval by Attimonelli, Matteo, Pomo, Claudio, Jannach, Dietmar, Tommaso Di Noia

    Published in arXiv.org
    Get full text
    Article
    Save to List
    Saved in:
  11. 11
    Top-N Recommendation Algorithms: A Quest for the State-of-the-Art

    Top-N Recommendation Algorithms: A Quest for the State-of-the-Art by Anelli, Vito Walter, Bellogín, Alejandro, Tommaso Di Noia, Jannach, Dietmar, Pomo, Claudio

    Published in arXiv.org
    Get full text
    Article
    Save to List
    Saved in:
  12. 12
    Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis

    Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis by Anelli, Vito Walter, Malitesta, Daniele, Pomo, Claudio, Bellogín, Alejandro, Tommaso Di Noia, Eugenio Di Sciascio

    Published in arXiv.org
    Get full text
    Article
    Save to List
    Saved in:
  13. 13
    Reenvisioning Collaborative Filtering vs Matrix Factorization

    Reenvisioning Collaborative Filtering vs Matrix Factorization by Anelli, Vito Walter, Bellogín, Alejandro, Tommaso Di Noia, Pomo, Claudio

    Published in arXiv.org
    Get full text
    Article
    Save to List
    Saved in:
  14. 14
    Ducho: A Unified Framework for the Extraction of Multimodal Features in Recommendation

    Ducho: A Unified Framework for the Extraction of Multimodal Features in Recommendation by Malitesta, Daniele, Gassi, Giuseppe, Pomo, Claudio, Tommaso Di Noia

    Published in arXiv.org
    Get full text
    Article
    Save to List
    Saved in:
  15. 15
    On Popularity Bias of Multimodal-aware Recommender Systems: a Modalities-driven Analysis

    On Popularity Bias of Multimodal-aware Recommender Systems: a Modalities-driven Analysis by Malitesta, Daniele, Cornacchia, Giandomenico, Pomo, Claudio, Tommaso Di Noia

    Published in arXiv.org
    Get full text
    Article
    Save to List
    Saved in:
  16. 16
    Ducho meets Elliot: Large-scale Benchmarks for Multimodal Recommendation

    Ducho meets Elliot: Large-scale Benchmarks for Multimodal Recommendation by Attimonelli, Matteo, Danese, Danilo, Angela Di Fazio, Malitesta, Daniele, Pomo, Claudio, Tommaso Di Noia

    Published in arXiv.org
    Get full text
    Article
    Save to List
    Saved in:
  17. 17
    Do We Really Need to Drop Items with Missing Modalities in Multimodal Recommendation?

    Do We Really Need to Drop Items with Missing Modalities in Multimodal Recommendation? by Malitesta, Daniele, Rossi, Emanuele, Pomo, Claudio, Tommaso Di Noia, Malliaros, Fragkiskos D

    Published in arXiv.org
    Get full text
    Article
    Save to List
    Saved in:
  18. 18
    GUapp: A Conversational Agent for Job Recommendation for the Italian Public Administration

    GUapp: A Conversational Agent for Job Recommendation for the Italian Public Administration by Bellini, Vito, Biancofiore, Giovanni Maria, Di Noia, Tommaso, Sciascio, Eugenio Di, Narducci, Fedelucio, Pomo, Claudio

    Request full text
    Conference Proceeding
    Save to List
    Saved in:
  19. 19
    Dealing with Missing Modalities in Multimodal Recommendation: a Feature Propagation-based Approach

    Dealing with Missing Modalities in Multimodal Recommendation: a Feature Propagation-based Approach by Malitesta, Daniele, Rossi, Emanuele, Pomo, Claudio, Malliaros, Fragkiskos D, Tommaso Di Noia

    Published in arXiv.org
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    Ducho 2.0: Towards a More Up-to-Date Unified Framework for the Extraction of Multimodal Features in Recommendation

    Ducho 2.0: Towards a More Up-to-Date Unified Framework for the Extraction of Multimodal Features in Recommendation by Attimonelli, Matteo, Danese, Danilo, Malitesta, Daniele, Pomo, Claudio, Gassi, Giuseppe, Tommaso Di Noia

    Published in arXiv.org
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: