Miao Zhang - RankMe

76 papers A* 18B 3C 1Journal 50Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	CVeDRL: An Efficient Code Verifier via Difficulty-aware Reinforcement Learning. CoRR Ji Shi, Peiming Guo, Meishan Zhang, Miao Zhang, Xuebo Liu, Min Zhang, Weili Guan
2026	J	`jnl`	Domain aware post training quantization for vision transformers in deployment. Pattern Recognit. Li Wang, Chao Zeng, Miao Zhang, Jianlong Wu, Liqiang Nie
2026	J	`jnl`	FRM-PTQ: Feature relationship matching enhanced low-bit post-training quantization for large language models. Neural Networks Chao Zeng, Jiaqi Zhao, Miao Zhang, Li Wang, Weili Guan, Liqiang Nie
2026	J	`jnl`	TINA: Text-Free Inversion Attack for Unlearned Text-to-Image Diffusion Models. CoRR Qianlong Xiang, Miao Zhang, Haoyu Zhang, Kun Wang, Junhui Hou, Liqiang Nie
2025	J	`jnl`	Benchmarking Post-Training Quantization in LLMs: Comprehensive Taxonomy, Unified Evaluation, and Comparative Analysis. CoRR Jiaqi Zhao, Ming Wang, Miao Zhang, Yuzhang Shang, Xuebo Liu, Yaowei Wang, Min Zhang, Liqiang Nie
2025	J	`jnl`	Boost Post-Training Quantization via Null Space Optimization for Large Language Models. CoRR Jiaqi Zhao, Miao Zhang, Weili Guan, Liqiang Nie
2025	A*	`conf`	Curriculum Coarse-to-Fine Selection for High-IPC Dataset Distillation. CVPR Yanda Chen, Gongwei Chen, Miao Zhang, Weili Guan, Liqiang Nie
2025	J	`jnl`	Curriculum Coarse-to-Fine Selection for High-IPC Dataset Distillation. CoRR Yanda Chen, Gongwei Chen, Miao Zhang, Weili Guan, Liqiang Nie
2025	A*	`conf`	DKDM: Data-Free Knowledge Distillation for Diffusion Models with Any Architecture. CVPR Qianlong Xiang, Miao Zhang, Yuzhang Shang, Jianlong Wu, Yan Yan, Liqiang Nie
2025	J	`jnl`	DiVE: Efficient Multi-View Driving Scenes Generation Based on Video Diffusion Transformer. CoRR Junpeng Jiang, Gangyi Hong, Miao Zhang, Hengtong Hu, Kun Zhan, Rui Shao, Liqiang Nie
2025	A*	`conf`	Enhancing Diversity for Data-free Quantization. CVPR Kai Zhao, Zhihao Zhuang, Miao Zhang, Chenjuan Guo, Yang Shu, Bin Yang
2025	J	`jnl`	LRQuant+: A Unified and Learnable Framework to Post-Training Quantization for Transformer-Based Large Foundation Models. IEEE Trans. Pattern Anal. Mach. Intell. Jiaqi Zhao, Chao Zeng, Ming Wang, Linxuan Han, Yuzhang Shang, Miao Zhang, Liqiang Nie
2025	—	`conf`	PTQ1.61: Push the Real Limit of Extremely Low-Bit Post-Training Quantization Methods for Large Language Models. ACL (1) Jiaqi Zhao, Miao Zhang, Ming Wang, Yuzhang Shang, Kaihao Zhang, Weili Guan, Yaowei Wang, Min Zhang
2025	J	`jnl`	PTQ1.61: Push the Real Limit of Extremely Low-Bit Post-Training Quantization Methods for Large Language Models. CoRR Jiaqi Zhao, Miao Zhang, Ming Wang, Yuzhang Shang, Kaihao Zhang, Weili Guan, Yaowei Wang, Min Zhang
2025	B	`conf`	SFi-Former: Sparse Flow Induced Attention for Graph Transformer. ICMR Zhonghao Li, Ji Shi, Xinming Zhang, Miao Zhang, Bo Li
2025	J	`jnl`	SFi-Former: Sparse Flow Induced Attention for Graph Transformer. CoRR Zhonghao Li, Ji Shi, Xinming Zhang, Miao Zhang, Bo Li
2025	J	`jnl`	SplitLoRA: Balancing Stability and Plasticity in Continual Learning Through Gradient Space Splitting. CoRR Haomiao Qiu, Miao Zhang, Ziyue Qiao, Weili Guan, Min Zhang, Liqiang Nie
2025	J	`jnl`	Train with Perturbation, Infer after Merging: A Two-Stage Framework for Continual Learning. CoRR Haomiao Qiu, Miao Zhang, Ziyue Qiao, Liqiang Nie
2025	J	`jnl`	Trained Mamba Emulates Online Gradient Descent in In-Context Linear Regression. CoRR Jiarui Jiang, Wei Huang, Miao Zhang, Taiji Suzuki, Liqiang Nie
2024	J	`jnl`	A Survey on Deep Neural Network Pruning: Taxonomy, Comparison, Analysis, and Recommendations. IEEE Trans. Pattern Anal. Mach. Intell. Hongrong Cheng, Miao Zhang, Javen Qinfeng Shi
2024	J	`jnl`	DKDM: Data-Free Knowledge Distillation for Diffusion Models with Any Architecture. CoRR Qianlong Xiang, Miao Zhang, Yuzhang Shang, Jianlong Wu, Yan Yan, Liqiang Nie
2024	J	`jnl`	Fully Automated Correlated Time Series Forecasting in Minutes. CoRR Xinle Wu, Xingjian Wu, Dalin Zhang, Miao Zhang, Chenjuan Guo, Bin Yang, Christian S. Jensen
2024	J	`jnl`	Fully Automated Correlated Time Series Forecasting in Minutes. Proc. VLDB Endow. Xinle Wu, Xingjian Wu, Dalin Zhang, Miao Zhang, Chenjuan Guo, Bin Yang, Christian S. Jensen
2024	J	`jnl`	Influence Function Based Second-Order Channel Pruning: Evaluating True Loss Changes for Pruning is Possible Without Retraining. IEEE Trans. Pattern Anal. Mach. Intell. Hongrong Cheng, Miao Zhang, Javen Qinfeng Shi
2024	—	`conf`	LRQuant: Learnable and Robust Post-Training Quantization for Large Language Models. ACL (1) Jiaqi Zhao, Miao Zhang, Chao Zeng, Ming Wang, Xuebo Liu, Liqiang Nie
2024	J	`jnl`	MINI-LLM: Memory-Efficient Structured Pruning for Large Language Models. CoRR Hongrong Cheng, Miao Zhang, Javen Qinfeng Shi
2024	J	`jnl`	QCore: Data-Efficient, On-Device Continual Calibration for Quantized Models - Extended Version. CoRR David Campos, Bin Yang, Tung Kieu, Miao Zhang, Chenjuan Guo, Christian S. Jensen
2024	J	`jnl`	QCore: Data-Efficient, On-Device Continual Calibration for Quantized Models. Proc. VLDB Endow. David Campos, Bin Yang, Tung Kieu, Miao Zhang, Chenjuan Guo, Christian S. Jensen
2024	A*	`conf`	Unveil Benign Overfitting for Transformer in Vision: Training Dynamics, Convergence, and Generalization. NeurIPS Jiarui Jiang, Wei Huang, Miao Zhang, Taiji Suzuki, Liqiang Nie
2024	J	`jnl`	Unveil Benign Overfitting for Transformer in Vision: Training Dynamics, Convergence, and Generalization. CoRR Jiarui Jiang, Wei Huang, Miao Zhang, Taiji Suzuki, Liqiang Nie
2023	J	`jnl`	A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations. CoRR Hongrong Cheng, Miao Zhang, Javen Qinfeng Shi
2023	J	`jnl`	Analyzing Deep PAC-Bayesian Learning with Neural Tangent Kernel: Convergence, Analytic Generalization Bound, and Efficient Hyperparameter Selection. Trans. Mach. Learn. Res. Wei Huang, Chunrui Liu, Yilan Chen, Richard Yi Da Xu, Miao Zhang, Tsui-Wei Weng
2023	A*	`conf`	Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs. WWW Xin Zheng, Miao Zhang, Chunyang Chen, Qin Zhang, Chuan Zhou, Shirui Pan
2023	J	`jnl`	Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs. CoRR Xin Zheng, Miao Zhang, Chunyang Chen, Qin Zhang, Chuan Zhou, Shirui Pan
2023	J	`jnl`	AutoCTS+: Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting. Proc. ACM Manag. Data Xinle Wu, Dalin Zhang, Miao Zhang, Chenjuan Guo, Bin Yang, Christian S. Jensen
2023	A*	`conf`	GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels. NeurIPS Xin Zheng, Miao Zhang, Chunyang Chen, Soheila Molaei, Chuan Zhou, Shirui Pan
2023	J	`jnl`	GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels. CoRR Xin Zheng, Miao Zhang, Chunyang Chen, Soheila Molaei, Chuan Zhou, Shirui Pan
2023	J	`jnl`	Influence Function Based Second-Order Channel Pruning-Evaluating True Loss Changes For Pruning Is Possible Without Retraining. CoRR Hongrong Cheng, Miao Zhang, Javen Qinfeng Shi
2023	J	`jnl`	LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation - Extended Version. CoRR David Campos, Miao Zhang, Bin Yang, Tung Kieu, Chenjuan Guo, Christian S. Jensen
2023	J	`jnl`	LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation. Proc. ACM Manag. Data David Campos, Miao Zhang, Bin Yang, Tung Kieu, Chenjuan Guo, Christian S. Jensen
2023	J	`jnl`	Multiple Time Series Forecasting with Dynamic Graph Modeling. Proc. VLDB Endow. Kai Zhao, Chenjuan Guo, Yunyao Cheng, Peng Han, Miao Zhang, Bin Yang
2023	A*	`conf`	Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data. NeurIPS Xin Zheng, Miao Zhang, Chunyang Chen, Quoc Viet Hung Nguyen, Xingquan Zhu, Shirui Pan
2023	J	`jnl`	Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data. CoRR Xin Zheng, Miao Zhang, Chunyang Chen, Quoc Viet Hung Nguyen, Xingquan Zhu, Shirui Pan
2022	J	`jnl`	AutoPINN: When AutoML Meets Physics-Informed Neural Networks. CoRR Xinle Wu, Dalin Zhang, Miao Zhang, Chenjuan Guo, Shuai Zhao, Yi Zhang, Huai Wang, Bin Yang
2022	A*	`conf`	BaLeNAS: Differentiable Architecture Search via the Bayesian Learning Rule. CVPR Miao Zhang, Shirui Pan, Xiaojun Chang, Steven Su, Jilin Hu, Gholamreza Haffari, Bin Yang
2022	J	`jnl`	Graph Neural Networks for Graphs with Heterophily: A Survey. CoRR Xin Zheng, Yixin Liu, Shirui Pan, Miao Zhang, Di Jin, Philip S. Yu
2022	A*	`conf`	Interpreting Operation Selection in Differentiable Architecture Search: A Perspective from Influence-Directed Explanations. NeurIPS Miao Zhang, Wei Huang, Bin Yang
2022	J	`jnl`	Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting. CoRR Xinle Wu, Dalin Zhang, Miao Zhang, Chenjuan Guo, Bin Yang, Christian S. Jensen
2022	A*	`conf`	Multi-Relational Graph Neural Architecture Search with Fine-grained Message Passing. ICDM Xin Zheng, Miao Zhang, Chunyang Chen, Chaojie Li, Chuan Zhou, Shirui Pan
2022	J	`jnl`	Pruning graph neural networks by evaluating edge properties. Knowl. Based Syst. Li Wang, Wei Huang, Miao Zhang, Shirui Pan, Xiaojun Chang, Steven Weidong Su
2022	A*	`conf`	Thrifty Neural Architecture Search for Medical Image Segmentation (Student Abstract). AAAI Ruibin Chen, Miao Zhang, Xin Zheng, Shirui Pan
2022	A*	`conf`	Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective. ICLR Wei Huang, Yayong Li, Weitao Du, Richard Y. D. Xu, Jie Yin, Ling Chen, Miao Zhang
2022	A*	`conf`	Weighted Mutual Learning with Diversity-Driven Model Compression. NeurIPS Miao Zhang, Li Wang, David Campos, Wei Huang, Chenjuan Guo, Bin Yang
2021	J	`jnl`	BaLeNAS: Differentiable Architecture Search via the Bayesian Learning Rule. CoRR Miao Zhang, Jilin Hu, Steven Su, Shirui Pan, Xiaojun Chang, Bin Yang, Gholamreza Haffari
2021	J	`jnl`	Convolutional Neural Networks-Based Lung Nodule Classification: A Surrogate-Assisted Evolutionary Algorithm for Hyperparameter Optimization. IEEE Trans. Evol. Comput. Miao Zhang, Huiqi Li, Shirui Pan, Juan Lyu, Steve S. H. Ling, Steven W. Su
2021	J	`jnl`	Differentiable Architecture Search Without Training Nor Labels: A Pruning Perspective. CoRR Miao Zhang, Steven W. Su, Shirui Pan, Xiaojun Chang, Wei Huang, Gholamreza Haffari
2021	J	`jnl`	One-Shot Neural Architecture Search: Maximising Diversity to Overcome Catastrophic Forgetting. IEEE Trans. Pattern Anal. Mach. Intell. Miao Zhang, Huiqi Li, Shirui Pan, Xiaojun Chang, Chuan Zhou, Zongyuan Ge, Steven Weidong Su
2021	A*	`conf`	iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients. ICML Miao Zhang, Steven W. Su, Shirui Pan, Xiaojun Chang, M. Ehsan Abbasnejad, Reza Haffari
2021	J	`jnl`	iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients. CoRR Miao Zhang, Steven W. Su, Shirui Pan, Xiaojun Chang, Ehsan Abbasnejad, Reza Haffari
2020	A*	`conf`	Differentiable Neural Architecture Search in Equivalent Space with Exploration Enhancement. NeurIPS Miao Zhang, Huiqi Li, Shirui Pan, Xiaojun Chang, Zongyuan Ge, Steven W. Su
2020	A*	`conf`	One-Shot Neural Architecture Search via Novelty Driven Sampling. IJCAI Miao Zhang, Huiqi Li, Shirui Pan, Taoping Liu, Steven W. Su
2020	A*	`conf`	Overcoming Multi-Model Forgetting in One-Shot NAS With Diversity Maximization. CVPR Miao Zhang, Huiqi Li, Shirui Pan, Xiaojun Chang, Steven W. Su
2019	J	`jnl`	Efficient Novelty-Driven Neural Architecture Search. CoRR Miao Zhang, Huiqi Li, Shirui Pan, Taoping Liu, Steven W. Su
2019	A*	`conf`	High Dimensional Bayesian Optimization via Supervised Dimension Reduction. IJCAI Miao Zhang, Huiqi Li, Steven W. Su
2019	J	`jnl`	High Dimensional Bayesian Optimization via Supervised Dimension Reduction. CoRR Miao Zhang, Huiqi Li, Steven W. Su
2019	J	`jnl`	Multi-level CNN for lung nodule classification with Gaussian Process assisted hyperparameter optimization. CoRR Miao Zhang, Huiqi Li, Juan Lyu, Sai-Ho Ling, Steven W. Su
2018	J	`jnl`	A New Multi-objective Evolutionary Algorithm for Inter-Cloud Service Composition. KSII Trans. Internet Inf. Syst. Li Liu, Shuxian Gu, Dongmei Fu, Miao Zhang, Rajkumar Buyya
2018	J	`jnl`	A reference direction and entropy based evolutionary algorithm for many-objective optimization. Appl. Soft Comput. Miao Zhang, Huiqi Li
2018	J	`jnl`	An adaptive multi-objective evolutionary algorithm for constrained workflow scheduling in Clouds. Distributed Parallel Databases Miao Zhang, Huiqi Li, Li Liu, Rajkumar Buyya
2018	—	`conf`	NOS.E: A New Fast Response Electronic Nose Health Monitoring System. EMBC Wentian Zhang, Taoping Liu, Miao Zhang, Yi Zhang, Huiqi Li, Maiken Ueland, Shari L. Forbes, X. Rosalind Wang, Steven W. Su
2017	J	`jnl`	Deadline-constrained coevolutionary genetic algorithm for scientific workflow scheduling in cloud computing. Concurr. Comput. Pract. Exp. Li Liu, Miao Zhang, Rajkumar Buyya, Qi Fan
2015	C	`conf`	Evolutionary Algorithm with AHP Decision-Making Method for Cloud Workflow Service Composition. CloudCom Miao Zhang, Li Liu
2015	—	`conf`	Genetic Algorithm Based QoS-aware Service Composition in Multi-cloud. CIC Miao Zhang, Li Liu, Songtao Liu
2015	J	`jnl`	Multi-objective Optimization Model with AHP Decision-making for Cloud Service Composition. KSII Trans. Internet Inf. Syst. Li Liu, Miao Zhang
2014	B	`conf`	A Survey on Workflow Management and Scheduling in Cloud Computing. CCGRID Li Liu, Miao Zhang, Yuqing Lin, Liangjuan Qin
2014	B	`conf`	Ontology-based service matching in cloud computing. FUZZ-IEEE Li Liu, Xiaofen Yao, Liangjuan Qin, Miao Zhang