Chao Chen

Orcid: 0000-0003-3911-8711

Affiliations:

Shanghai Jiao Tong University, China
IBM Research - China, Shanghai, China (former)
University of Colorado Boulder, USA (former)

According to our database¹, Chao Chen authored at least 20 papers between 2015 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Article

PhD thesis

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Bibliography

2024

EasyDGL: Encode, Train and Interpret for Continuous-Time Dynamic Graph Learning.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., December, 2024

Constructing and Masking Preference Profile with LLMs for Filtering Discomforting Recommendation.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Pyramid Graph Neural Network: A Graph Sampling and Filtering Approach for Multi-scale Disentangled Representations.

[BibT_eX]

[DOI]

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Graph Signal Sampling for Inductive One-Bit Matrix Completion: a Closed-form Solution.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Modeling Dynamic User Preference via Dictionary Learning for Sequential Recommendation.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2022

2021

Mixture Matrix Approximation for Collaborative Filtering.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2021

NeuSE: A Neural Snapshot Ensemble Method for Collaborative Filtering.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2021

Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Scalable and Explainable 1-Bit Matrix Completion via Graph Signal Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019

Collaborative Filtering with Noisy Ratings.

[BibT_eX]

[DOI]

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Synergizing Local and Global Models for Matrix Approximation.

[BibT_eX]

[DOI]

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018

Collaborative Filtering with Stability.

[BibT_eX]

[DOI]

CoRR, 2018

AdaError: An Adaptive Learning Rate Method for Matrix Approximation-based Collaborative Filtering.

[BibT_eX]

[DOI]

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

2017

Mixture-Rank Matrix Approximation for Collaborative Filtering.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

ERMMA: Expected Risk Minimization for Matrix Approximation-based Recommender Systems.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

GLOMA: Embedding Global Information in Local Matrix Approximation Models for Collaborative Filtering.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

An algorithm for efficient privacy-preserving item-based collaborative filtering.

[BibT_eX]

[DOI]

Future Gener. Comput. Syst., 2016

MPMA: Mixture Probabilistic Matrix Approximation for Collaborative Filtering.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Low-Rank Matrix Approximation with Stability.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

WEMAREC: Accurate and Scalable Recommendation through Weighted and Ensemble Matrix Approximation.

[BibT_eX]

[DOI]

Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2015

Chao Chen

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