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ORCIDPeng Han 0005
Person information
- affiliation: University of Electronic Science and Technology of China, China
- affiliation: Aalborg University, Denmark
- affiliation: King Abdullah University of Science and Technology, Saudi Arabia
Other persons with the same name
- Peng Han — disambiguation page
- Peng Han 0001
![[0000-0001-8675-9656]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-8675-9656")
— Ohio State University, Center for High Performance Power Electronics, Columbus, OH, USA (and 1 more) - Peng Han 0002 — Southern University of Science and Technology, Department of Earth and Space Science, Shenzhen, China
- Peng Han 0003 — National Digital Switching System Engineering and Technological Research Center, Zhengzhou, China
- Peng Han 0004 — Inner Mongolia University of Science and Technology, School of Information Engineering, Baotou, China
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2020 – today
- 2024
[j14]Peng Han, Xiangliang Zhang:
VGE: Gene-Disease Association by Variational Graph Embedding. Int. J. Crowd Sci. 8(2): 95-99 (2024)- [j13]Aiping Huang, Zihan Fang, Zhihao Wu, Yanchao Tan, Peng Han, Shiping Wang, Le Zhang:
Multi-view heterogeneous graph learning with compressed hypergraph neural networks. Neural Networks 179: 106562 (2024) - [j12]Jiangfeng Du, Silin Zhou, Jie Yu, Peng Han, Shuo Shang:
Cross-Task Multimodal Reinforcement for Long Tail Next POI Recommendation. IEEE Trans. Multim. 26: 1996-2005 (2024) - [c24]Peng Tang, Zhiqiang Xu, Chunlai Zhou, Pengfei Wei, Peng Han, Xin Cao, Tobias Lasser:
Prior and Prediction Inverse Kernel Transformer for Single Image Defocus Deblurring. AAAI 2024: 5145-5153 - [c23]Zhen Chen, Dalin Zhang, Shanshan Feng, Kaixuan Chen, Lisi Chen, Peng Han, Shuo Shang:
KGTS: Contrastive Trajectory Similarity Learning over Prompt Knowledge Graph Embedding. AAAI 2024: 8311-8319 - [c22]Minbo Ma, Jilin Hu, Christian S. Jensen, Fei Teng, Peng Han, Zhiqiang Xu, Tianrui Li:
Learning Time-Aware Graph Structures for Spatially Correlated Time Series Forecasting. ICDE 2024: 4435-4448 - [c21]Di Yao, Jin Wang, Wenjie Chen, Fangda Guo, Peng Han, Jingping Bi:
Deep Dirichlet Process Mixture Model for Non-parametric Trajectory Clustering. ICDE 2024: 4449-4462 - [i10]Siqi Fan, Xin Jiang, Xiang Li, Xuying Meng, Peng Han, Shuo Shang, Aixin Sun, Yequan Wang, Zhongyuan Wang:
Not all Layers of LLMs are Necessary during Inference. CoRR abs/2403.02181 (2024) - [i9]Shen Gao, Yifan Wang, Jiabao Fang, Lisi Chen, Peng Han, Shuo Shang:
DRE: Generating Recommendation Explanations by Aligning Large Language Models at Data-level. CoRR abs/2404.06311 (2024) - [i8]Chengrui Huang, Zhengliang Shi, Yuntao Wen, Xiuying Chen, Peng Han, Shen Gao, Shuo Shang:
What Affects the Stability of Tool Learning? An Empirical Study on the Robustness of Tool Learning Frameworks. CoRR abs/2407.03007 (2024) - [i7]Chang Gong, Di Yao, Jin Wang, Wenbin Li, Lanting Fang, Yongtao Xie, Kaiyu Feng, Peng Han, Jingping Bi:
PORCA: Root Cause Analysis with Partially Observed Data. CoRR abs/2407.05869 (2024) - [i6]Yiqun Yao, Wenjia Ma, Xuezhi Fang, Xin Jiang, Xiang Li, Xuying Meng, Peng Han, Jing Li, Aixin Sun, Yequan Wang:
Open-domain Implicit Format Control for Large Language Model Generation. CoRR abs/2408.04392 (2024) - [i5]Xin Jiang, Xiang Li, Wenjia Ma, Xuezhi Fang, Yiqun Yao, Naitong Yu, Xuying Meng, Peng Han, Jing Li, Aixin Sun, Yequan Wang:
Sketch: A Toolkit for Streamlining LLM Operations. CoRR abs/2409.03346 (2024) - [i4]Duc Kieu, Tung Kieu, Peng Han, Bin Yang, Christian S. Jensen, Bac Le:
TEAM: Topological Evolution-aware Framework for Traffic Forecasting-Extended Version. CoRR abs/2410.19192 (2024) - 2023
- [j11]Peng Han, Silin Zhou, Jie Yu, Zichen Xu, Lisi Chen, Shuo Shang:
Personalized Re-ranking for Recommendation with Mask Pretraining. Data Sci. Eng. 8(4): 357-367 (2023) - [j10]Kai Zhao, Chenjuan Guo, Yunyao Cheng, Peng Han, Miao Zhang, Bin Yang:
Multiple Time Series Forecasting with Dynamic Graph Modeling. Proc. VLDB Endow. 17(4): 753-765 (2023) - [j9]Jing Li, Peng Han, Xiangnan Ren, Jilin Hu, Lisi Chen, Shuo Shang:
Sequence Labeling With Meta-Learning. IEEE Trans. Knowl. Data Eng. 35(3): 3072-3086 (2023) - [j8]Silin Zhou, Peng Han, Di Yao, Lisi Chen, Xiangliang Zhang:
Spatial-temporal fusion graph framework for trajectory similarity computation. World Wide Web (WWW) 26(4): 1501-1523 (2023) - [j7]Siqi Fan, Yequan Wang, Xiaobing Pang, Lisi Chen, Peng Han, Shuo Shang:
UaMC: user-augmented conversation recommendation via multi-modal graph learning and context mining. World Wide Web (WWW) 26(6): 4109-4129 (2023) - [c20]Feiyu Yin, Yong Liu, Zhiqi Shen, Lisi Chen, Shuo Shang, Peng Han:
Next POI Recommendation with Dynamic Graph and Explicit Dependency. AAAI 2023: 4827-4834 - [c19]Silin Zhou, Jing Li, Hao Wang, Shuo Shang, Peng Han:
GRLSTM: Trajectory Similarity Computation with Graph-Based Residual LSTM. AAAI 2023: 4972-4980 - [c18]Silin Zhou, Dan He, Lisi Chen, Shuo Shang, Peng Han:
Heterogeneous Region Embedding with Prompt Learning. AAAI 2023: 4981-4989 - [c17]Xiaobing Pang, Yequan Wang, Siqi Fan, Lisi Chen, Shuo Shang, Peng Han:
EmpMFF: A Multi-factor Sequence Fusion Framework for Empathetic Response Generation. WWW 2023: 1754-1764 - [i3]Xiang Li, Yiqun Yao, Xin Jiang, Xuezhi Fang, Xuying Meng, Siqi Fan, Peng Han, Jing Li, Li Du, Bowen Qin, Zheng Zhang, Aixin Sun, Yequan Wang:
FLM-101B: An Open LLM and How to Train It with $100K Budget. CoRR abs/2309.03852 (2023) - [i2]Minbo Ma, Jilin Hu, Christian S. Jensen, Fei Teng, Peng Han, Zhiqiang Xu, Tianrui Li:
Learning Time-aware Graph Structures for Spatially Correlated Time Series Forecasting. CoRR abs/2312.16403 (2023) - 2022
- [j6]Peng Han, Shuo Shang, Aixin Sun, Peilin Zhao, Kai Zheng, Xiangliang Zhang:
Point-of-Interest Recommendation With Global and Local Context. IEEE Trans. Knowl. Data Eng. 34(11): 5484-5495 (2022) - [c16]Peng Han, Peilin Zhao, Chan Lu, Junzhou Huang, Jiaxiang Wu, Shuo Shang, Bin Yao, Xiangliang Zhang:
GNN-Retro: Retrosynthetic Planning with Graph Neural Networks. AAAI 2022: 4014-4021 - [c15]Xiaochuan Gou, Peng Han, Xiangliang Zhang:
QuoGNN: Quotient Graph Neural Network for Urban Flow Forecasting. IEEE Big Data 2022: 727-733 - [c14]Xuan Rao, Hao Wang, Liang Zhang, Jing Li, Shuo Shang, Peng Han:
FOGS: First-Order Gradient Supervision with Learning-based Graph for Traffic Flow Forecasting. IJCAI 2022: 3926-3932 - [c13]Siqi Fan, Yequan Wang, Jing Li, Zheng Zhang, Shuo Shang, Peng Han:
Interactive Information Extraction by Semantic Information Graph. IJCAI 2022: 4100-4106 - [c12]Dachuan Liu, Jin Wang, Shuo Shang, Peng Han:
MSDR: Multi-Step Dependency Relation Networks for Spatial Temporal Forecasting. KDD 2022: 1042-1050 - [c11]Xuan Rao, Lisi Chen, Yong Liu, Shuo Shang, Bin Yao, Peng Han:
Graph-Flashback Network for Next Location Recommendation. KDD 2022: 1463-1471 - [c10]Shufang Xie, Rui Yan, Peng Han, Yingce Xia, Lijun Wu, Chenjuan Guo, Bin Yang, Tao Qin:
RetroGraph: Retrosynthetic Planning with Graph Search. KDD 2022: 2120-2129 - [c9]Peng Han, Shuo Shang:
Scene Re-ranking for Recommendation. MMSP 2022: 1-6 - [i1]Shufang Xie, Rui Yan, Peng Han, Yingce Xia, Lijun Wu, Chenjuan Guo, Bin Yang, Tao Qin:
RetroGraph: Retrosynthetic Planning with Graph Search. CoRR abs/2206.11477 (2022) - 2021
- [j5]Yuxi Hong, Peng Han:
LSDDL: Layer-Wise Sparsification for Distributed Deep Learning. Big Data Res. 26: 100272 (2021) - [c8]Peng Han, Jin Wang, Di Yao, Shuo Shang, Xiangliang Zhang:
A Graph-based Approach for Trajectory Similarity Computation in Spatial Networks. KDD 2021: 556-564 - 2020
- [j4]Hao Wang, Yuan-Yuan Yang, Yang Pan, Peng Han, Zhong-Xiao Li, He-Guang Huang, Shun-Zhi Zhu:
Detecting thoracic diseases via representation learning with adaptive sampling. Neurocomputing 406: 354-360 (2020) - [c7]Peng Han, Zhongxiao Li, Yong Liu, Peilin Zhao, Jing Li, Hao Wang, Shuo Shang:
Contextualized Point-of-Interest Recommendation. IJCAI 2020: 2484-2490 - [c6]Yinan Zhang, Yong Liu, Peng Han, Chunyan Miao, Lizhen Cui, Baoli Li, Haihong Tang:
Learning Personalized Itemset Mapping for Cross-Domain Recommendation. IJCAI 2020: 2561-2567
2010 – 2019
- 2019
- [c5]Peng Han, Shuo Shang, Aixin Sun, Peilin Zhao, Kai Zheng, Panos Kalnis:
AUC-MF: Point of Interest Recommendation with AUC Maximization. ICDE 2019: 1558-1561 - [c4]Peng Han, Peng Yang, Peilin Zhao, Shuo Shang, Yong Liu, Jiayu Zhou, Xin Gao, Panos Kalnis:
GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization. KDD 2019: 705-713 - 2018
- [j3]Aoxue Li, Zhiwu Lu, Liwei Wang, Peng Han, Ji-Rong Wen:
Large-Scale Sparse Learning From Noisy Tags for Semantic Segmentation. IEEE Trans. Cybern. 48(1): 253-263 (2018) - 2017
- [j2]Zhiwu Lu, Zhenyong Fu, Tao Xiang, Peng Han, Liwei Wang, Xin Gao:
Learning from Weak and Noisy Labels for Semantic Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 39(3): 486-500 (2017) - [c3]Guangzhen Liu, Peng Han, Yulei Niu, Wenwu Yuan, Zhiwu Lu, Ji-Rong Wen:
Graph-boosted convolutional neural networks for semantic segmentation. IJCNN 2017: 612-618 - 2016
- [c2]Peng Han, Guangzhen Liu, Songfang Huang, Wenwu Yuan, Zhiwu Lu:
Segmentation with Selectively Propagated Constraints. ICONIP (2) 2016: 585-592 - 2015
- [j1]Zhiwu Lu, Peng Han, Liwei Wang, Ji-Rong Wen:
Semantic Sparse Recoding of Visual Content for Image Applications. IEEE Trans. Image Process. 24(1): 176-188 (2015) - [c1]Yulei Niu, Zhiwu Lu, Songfang Huang, Peng Han, Ji-Rong Wen:
Weakly Supervised Matrix Factorization for Noisily Tagged Image Parsing. IJCAI 2015: 3749-3755
Coauthor Index
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last updated on 2024-12-19 23:08 CET by the dblp team
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