Ji Cheng

Orcid: 0000-0002-1123-6030

Affiliations:

City University of Hong Kong (CityUHK), Department of Computer Science, Kowloon Tong, Hong Kong (since 2023)
City University of Hong Kong Shenzhen (CUHK-SZ), Shenzhen, China
Huazhong University of Science and Technology, School of Mechanical Science and Engineering, Wuhan, China (former 2014-2021)

According to our database¹, Ji Cheng authored at least 14 papers between 2021 and 2026.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Bibliography

2026

Parametric Pareto Set Learning for Expensive Multi-Objective Optimization.

[BibT_eX]

[DOI]

Ji Cheng

Bo Xue

Qingfu Zhang

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

Offline Multi-Objective Bandits: From Logged Data to Pareto-Optimal Policies.

[BibT_eX]

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Lexicographic Lipschitz Bandits: New Algorithms and a Lower Bound.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2025

Neural Evolution Strategy for Black-box Pareto Set Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Multi-Objective Neural Bandits with Random Scalarization.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Multi-objective Linear Reinforcement Learning with Lexicographic Rewards.

[BibT_eX]

[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Practical multi-fidelity machine learning: fusion of deterministic and Bayesian models.

[BibT_eX]

[DOI]

Jiaxiang Yi

Ji Cheng

Miguel A. Bessa

CoRR, 2024

Diffusion-based Contrastive Learning for Sequential Recommendation.

[BibT_eX]

[DOI]

CoRR, 2024

Evolve Cost-Aware Acquisition Functions Using Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

Provably Neural Active Learning Succeeds via Prioritizing Perplexing Samples.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Context Matters: Enhancing Sequential Recommendation with Context-aware Diffusion-based Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Multiobjective Lipschitz Bandits under Lexicographic Ordering.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Hierarchize Pareto Dominance in Multi-Objective Stochastic Linear Bandits.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2021

A parallel constrained lower confidence bounding approach for computationally expensive constrained optimization problems.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2021

Ji Cheng

Timeline

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Bibliography

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