Pan Li

Orcid: 0000-0003-4957-3064

Affiliations:
  • New York University, NY, USA


According to our database1, Pan Li authored at least 16 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2024
Dual Contrastive Learning for Efficient Static Feature Representation in Sequential Recommendations.
IEEE Trans. Knowl. Data Eng., February, 2024

When Variety Seeking Meets Unexpectedness: Incorporating Variety-Seeking Behaviors into Design of Unexpected Recommender Systems.
Inf. Syst. Res., 2024

2023
Don't Need All Eggs in One Basket: Reconstructing Composite Embeddings of Customers from Individual-Domain Embeddings.
ACM Trans. Manag. Inf. Syst., June, 2023

Adversarial Learning for Cross Domain Recommendations.
ACM Trans. Intell. Syst. Technol., February, 2023

Dual Metric Learning for Effective and Efficient Cross-Domain Recommendations.
IEEE Trans. Knowl. Data Eng., 2023

2022
Learning Latent Multi-Criteria Ratings From User Reviews for Recommendations.
IEEE Trans. Knowl. Data Eng., 2022

2021
Leveraging Multi-Faceted User Preferences for Improving Click-Through Rate Predictions.
Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Dual Attentive Sequential Learning for Cross-Domain Click-Through Rate Prediction.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020
Latent Unexpected Recommendations.
ACM Trans. Intell. Syst. Technol., 2020

Hybrid Utility Function for Unexpected Recommendations.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

DDTCDR: Deep Dual Transfer Cross Domain Recommendation.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

PURS: Personalized Unexpected Recommender System for Improving User Satisfaction.
Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

2019
Latent Unexpected and Useful Recommendation.
CoRR, 2019

Latent multi-criteria ratings for recommendations.
Proceedings of the 13th ACM Conference on Recommender Systems, 2019

Latent Modeling of Unexpectedness for Recommendations.
Proceedings of ACM RecSys 2019 Late-Breaking Results co-located with the 13th ACM Conference on Recommender Systems, 2019

Towards Controllable and Personalized Review Generation.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019


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