A parallel constrained lower confidence bounding approach for computationally expensive constrained optimization problems. - Ji Cheng 001; Ping Jiang 005; Qi Zhou 006; Jiexiang Hu; Leshi Shu (Appl. Soft Comput., 2021)

Hierarchize Pareto Dominance in Multi-Objective Stochastic Linear Bandits. - Ji Cheng 001; Bo Xue 004; Jiaxiang Yi; Qingfu Zhang 001 (AAAI, 2024)

Multiobjective Lipschitz Bandits under Lexicographic Ordering. - Bo Xue 004; Ji Cheng 001; Fei Liu 044; Yimu Wang; Qingfu Zhang 001 (AAAI, 2024)

Context Matters: Enhancing Sequential Recommendation with Context-aware Diffusion-based Contrastive Learning. - Ziqiang Cui; Haolun Wu; Bowei He; Ji Cheng 001; Chen Ma 001 (CIKM, 2024)

Provably Neural Active Learning Succeeds via Prioritizing Perplexing Samples. - Dake Bu; Wei Huang 034; Taiji Suzuki; Ji Cheng 001; Qingfu Zhang 001; Zhiqiang Xu 003; Hau-San Wong (ICML, 2024)

Evolve Cost-Aware Acquisition Functions Using Large Language Models. - Yiming Yao; Fei Liu 044; Ji Cheng 001; Qingfu Zhang 001 (PPSN (2), 2024)

Diffusion-based Contrastive Learning for Sequential Recommendation. - Ziqiang Cui; Haolun Wu; Bowei He; Ji Cheng 001; Chen Ma 001 (CoRR, 2024)

Practical multi-fidelity machine learning: fusion of deterministic and Bayesian models. - Jiaxiang Yi; Ji Cheng 001; Miguel A. Bessa (CoRR, 2024)