Lyu, Yueming

18 publications

ICML 2025 Diversifying Policy Behaviors with Extrinsic Behavioral Curiosity Zhenglin Wan, Xingrui Yu, David Mark Bossens, Yueming Lyu, Qing Guo, Flint Xiaofeng Fan, Yew-Soon Ong, Ivor Tsang

ICLR 2025 Fast Direct: Query-Efficient Online Black-Box Guidance for Diffusion-Model Target Generation Kim Yong Tan, Yueming Lyu, Ivor Tsang, Yew-Soon Ong

NeurIPS 2025 GOOD: Training-Free Guided Diffusion Sampling for Out-of-Distribution Detection Xin Gao, Jiyao Liu, Guanghao Li, Yueming Lyu, Jianxiong Gao, Weichen Yu, Ningsheng Xu, Liang Wang, Caifeng Shan, Ziwei Liu, Chenyang Si

TMLR 2025 Graph Potential Field Neural Network for Massive Agents Group-Wise Path Planning Yueming Lyu, Xiaowei Zhou, Xingrui Yu, Ivor Tsang

ICLR 2025 Image-Level Memorization Detection via Inversion-Based Inference Perturbation Yue Jiang, Haokun Lin, Yang Bai, Bo Peng, Zhili Liu, Yueming Lyu, Yong Yang, Xingzheng, Jing Dong

NeurIPS 2025 InstructFlow: Adaptive Symbolic Constraint-Guided Code Generation for Long-Horizon Planning Haotian Chi, Zeyu Feng, Yueming Lyu, Chengqi Zheng, Linbo Luo, Yew-Soon Ong, Ivor Tsang, Hechang Chen, Yi Chang, Haiyan Yin

ICLRW 2025 Nonparametric Distributional Black-Box Optimization via Diffusion Process Yueming Lyu, Atsushi Nitanda, Ivor Tsang

ICLR 2025 Sharpness-Aware Black-Box Optimization Feiyang Ye, Yueming Lyu, Xuehao Wang, Masashi Sugiyama, Yu Zhang, Ivor Tsang

ICLR 2024 Adaptive Stochastic Gradient Algorithm for Black-Box Multi-Objective Learning Feiyang Ye, Yueming Lyu, Xuehao Wang, Yu Zhang, Ivor Tsang

ICML 2024 Diversified Batch Selection for Training Acceleration Feng Hong, Yueming Lyu, Jiangchao Yao, Ya Zhang, Ivor Tsang, Yanfeng Wang

ICLR 2024 On Harmonizing Implicit Subpopulations Feng Hong, Jiangchao Yao, Yueming Lyu, Zhihan Zhou, Ivor Tsang, Ya Zhang, Yanfeng Wang

NeurIPS 2023 Fast Rank-1 Lattice Targeted Sampling for Black-Box Optimization Yueming Lyu

ECML-PKDD 2021 Black-Box Optimizer with Stochastic Implicit Natural Gradient Yueming Lyu, Ivor W. Tsang

ICLR 2020 Curriculum Loss: Robust Learning and Generalization Against Label Corruption Yueming Lyu, Ivor W. Tsang

ICML 2020 Intrinsic Reward Driven Imitation Learning via Generative Model Xingrui Yu, Yueming Lyu, Ivor Tsang

NeurIPS 2020 Subgroup-Based Rank-1 Lattice Quasi-Monte Carlo Yueming Lyu, Yuan Yuan, Ivor W. Tsang

ICLR 2019 Marginalized Average Attentional Network for Weakly-Supervised Learning Yuan Yuan, Yueming Lyu, Xi Shen, Ivor W. Tsang, Dit-Yan Yeung

ICML 2017 Spherical Structured Feature Maps for Kernel Approximation Yueming Lyu