Ji Cheng

16 papers A* 7A 1Journal 7Unranked 1
YearRankTypeTitle / Venue / Authors
2026 A* conf
Offline Multi-Objective Bandits: From Logged Data to Pareto-Optimal Policies.
AAAI
Ji Cheng, Song Lai, Shunyu Yao, Bo Xue
2026 A* conf
Parametric Pareto Set Learning for Expensive Multi-Objective Optimization.
AAAI
Ji Cheng, Bo Xue, Qingfu Zhang
2025 J jnl
Lexicographic Lipschitz Bandits: New Algorithms and a Lower Bound.
J. Mach. Learn. Res.
Bo Xue, Ji Cheng, Fei Liu, Yimu Wang, Lijun Zhang, Qingfu Zhang
2025 A* conf
Multi-Objective Neural Bandits with Random Scalarization.
IJCAI
Ji Cheng, Bo Xue, Chengyu Lu, Ziqiang Cui, Qingfu Zhang
2025 A* conf
Multi-objective Linear Reinforcement Learning with Lexicographic Rewards.
ICML
Bo Xue, Dake Bu, Ji Cheng, Yuanyu Wan, Qingfu Zhang
2025 J jnl
Parametric Pareto Set Learning for Expensive Multi-Objective Optimization.
CoRR
Ji Cheng, Bo Xue, Qingfu Zhang
2024 A conf
Context Matters: Enhancing Sequential Recommendation with Context-aware Diffusion-based Contrastive Learning.
CIKM
Ziqiang Cui, Haolun Wu, Bowei He, Ji Cheng, Chen Ma
2024 J jnl
Diffusion-based Contrastive Learning for Sequential Recommendation.
CoRR
Ziqiang Cui, Haolun Wu, Bowei He, Ji Cheng, Chen Ma
2024 — conf
Evolve Cost-Aware Acquisition Functions Using Large Language Models.
PPSN (2)
Yiming Yao, Fei Liu, Ji Cheng, Qingfu Zhang
2024 J jnl
Evolve Cost-aware Acquisition Functions Using Large Language Models.
CoRR
Yiming Yao, Fei Liu, Ji Cheng, Qingfu Zhang
2024 A* conf
Hierarchize Pareto Dominance in Multi-Objective Stochastic Linear Bandits.
AAAI
Ji Cheng, Bo Xue, Jiaxiang Yi, Qingfu Zhang
2024 A* conf
Multiobjective Lipschitz Bandits under Lexicographic Ordering.
AAAI
Bo Xue, Ji Cheng, Fei Liu, Yimu Wang, Qingfu Zhang
2024 J jnl
Practical multi-fidelity machine learning: fusion of deterministic and Bayesian models.
CoRR
Jiaxiang Yi, Ji Cheng, Miguel A. Bessa
2024 A* conf
Provably Neural Active Learning Succeeds via Prioritizing Perplexing Samples.
ICML
Dake Bu, Wei Huang, Taiji Suzuki, Ji Cheng, Qingfu Zhang, Zhiqiang Xu, Hau-San Wong
2024 J jnl
Provably Neural Active Learning Succeeds via Prioritizing Perplexing Samples.
CoRR
Dake Bu, Wei Huang, Taiji Suzuki, Ji Cheng, Qingfu Zhang, Zhiqiang Xu, Hau-San Wong
2021 J jnl
A parallel constrained lower confidence bounding approach for computationally expensive constrained optimization problems.
Appl. Soft Comput.
Ji Cheng, Ping Jiang, Qi Zhou, Jiexiang Hu, Leshi Shu