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16th KSEM 2023: Guangzhou, China - Part I
- Zhi Jin, Yuncheng Jiang, Robert Andrei Buchmann, Yaxin Bi, Ana-Maria Ghiran, Wenjun Ma:
Knowledge Science, Engineering and Management - 16th International Conference, KSEM 2023, Guangzhou, China, August 16-18, 2023, Proceedings, Part I. Lecture Notes in Computer Science 14117, Springer 2023, ISBN 978-3-031-40282-1
Knowledge Science with Learning and AI
- Zeqian Wei, Hui Kang, Hongjuan Li, Geng Sun, Jiahui Li, Xinyu Bao, Bo Zhu:
Joint Feature Selection and Classifier Parameter Optimization: A Bio-Inspired Approach. 3-14 - Kai Shen, Haoyu Wang, Arin Chaudhuri, Zohreh Asgharzadeh:
Automatic Gaussian Bandwidth Selection for Kernel Principal Component Analysis. 15-26 - Junjie Hu, Chenyou Fan, Hualie Jiang, Xiyue Guo, Yuan Gao, Xiangyong Lu, Tin Lun Lam:
Boosting LightWeight Depth Estimation via Knowledge Distillation. 27-39 - Mengying Guo, Zhenyu Sun, Yuyi Wang, Xingwu Liu:
Graph Neural Network with Neighborhood Reconnection. 40-50 - Lianwei Qu, Yong Wang, Jing Yang:
Critical Node Privacy Protection Based on Random Pruning of Critical Trees. 51-58 - Peihao Ding, Yan Tang, Yingpei Chen, Xiaobing Li:
DSEAformer: Forecasting by De-stationary Autocorrelation with Edgebound. 59-65 - Kaifang Dong, Fuyong Xu, Baoxing Jiang, Hongye Li, Peiyu Liu:
Multitask-Based Cluster Transmission for Few-Shot Text Classification. 66-77 - Yadan Han, Guangquan Lu, Jiecheng Li, Fuqing Ling, Wanxi Chen, Liang Zhang:
Hyperplane Knowledge Graph Embedding with Path Neighborhoods and Mapping Properties. 78-91 - Qiyun Fan, Yan Tang, Xiaoming Ding, Qianglong Huangfu, Peihao Ding:
RTAD-TP: Real-Time Anomaly Detection Algorithm for Univariate Time Series Data Based on Two-Parameter Estimation. 92-101 - Jiamei Feng, Mengchi Liu, Tingkun Nie, Caixia Zhou:
Multi-Sampling Item Response Ranking Neural Cognitive Diagnosis with Bilinear Feature Interaction. 102-113 - Tiechui Yao, Jue Wang, Junyu Gu, Yumeng Shi, Fang Liu, Xiaoguang Wang, Yangang Wang, Xuebin Chi:
A Sparse Matrix Optimization Method for Graph Neural Networks Training. 114-123 - Jie Cui, Fei Pu, Bailin Yang:
Dual-Dimensional Refinement of Knowledge Graph Embedding Representation. 124-137 - Tian Wang, Zhiguang Wang, Rongliang Wang, Dawei Li, Qiang Lu:
Contextual Information Augmented Few-Shot Relation Extraction. 138-149 - Long Chen, Mingjian Guang, Junli Wang, Chungang Yan:
Dynamic and Static Feature-Aware Microservices Decomposition via Graph Neural Networks. 150-163 - Haijia Bao, Yu Du, Ya Li:
An Enhanced Fitness-Distance Balance Slime Mould Algorithm and Its Application in Feature Selection. 164-178 - Hong Jia, Jian Huang:
Low Redundancy Learning for Unsupervised Multi-view Feature Selection. 179-190 - Chengkai Piao, Yuchen Wang, Jinmao Wei:
Dynamic Feed-Forward LSTM. 191-202 - Qin Sun, Zheng Yang, Zhiming Liu, Quan Zou:
Black-Box Adversarial Attack on Graph Neural Networks Based on Node Domain Knowledge. 203-217 - Jieya Peng, Jiale Xu, Ya Li:
Role and Relationship-Aware Representation Learning for Complex Coupled Dynamic Heterogeneous Networks. 218-233 - Yi Liang, Shuai Zhao, Bo Cheng, Hao Yang:
Twin Graph Attention Network with Evolution Pattern Learner for Few-Shot Temporal Knowledge Graph Completion. 234-246 - Hong Jia, Menghan Dong:
Subspace Clustering with Feature Grouping for Categorical Data. 247-254 - Jun Hu, Jinyan Wang, Quanmin Wei, Du Kai, Xianxian Li:
Learning Graph Neural Networks on Feature-Missing Graphs. 255-262 - Ruiyin Yang, Xiao Wei:
Dealing with Over-Reliance on Background Graph for Few-Shot Knowledge Graph Completion. 263-275 - Yuhang Liu, Yi Zhang, Yang Cao, Ye Zhu, Nayyar Zaidi, Chathu Ranaweera, Gang Li, Qingyi Zhu:
Kernel-Based Feature Extraction for Time Series Clustering. 276-283 - Simon Schramm, Ulrich Niklas, Ute Schmid:
Cluster Robust Inference for Embedding-Based Knowledge Graph Completion. 284-299 - Yafang Li, Wenbo Wang, Guixiang Ma, Baokai Zu:
Community-Enhanced Contrastive Siamese Networks for Graph Representation Learning. 300-314 - Yang Zou, Qifei Wang, Zhen Wang, Jian Zhou, Xiaoqin Zeng:
Distant Supervision Relation Extraction with Improved PCNN and Multi-level Attention. 315-327 - Keke Tang, Tianrui Lou, Xu He, Yawen Shi, Peican Zhu, Zhaoquan Gu:
Enhancing Adversarial Robustness via Anomaly-aware Adversarial Training. 328-342 - Wen Zhang, Zhengjiang Liu, Yan Xue, Ruibo Wang, Xuefei Cao, Jihong Li:
An Improved Cross-Validated Adversarial Validation Method. 343-353 - Jiuqiang Li:
EACCNet: Enhanced Auto-Cross Correlation Network for Few-Shot Classification. 354-365 - Qianqian Peng, Ziming Tang, Xinzhi Yao, Sizhuo Ouyang, Zhihan He, Jingbo Xia:
A Flexible Generative Model for Joint Label-Structure Estimation from Multifaceted Graph Data. 366-378 - Tengwei Song, Long Yin, Xudong Ma, Jie Luo:
Dual Channel Knowledge Graph Embedding with Ontology Guided Data Augmentation. 379-392 - Jiayang Wu, Zhenlian Qi, Wensheng Gan:
Multi-Dimensional Graph Rule Learner. 393-404 - Ziyan Ke, Lingxi Peng, Yiduan Chen, Jie Liu, Xuebing Luo, Jinhui Lin, Zhiwen Yu:
MixUNet: A Hybrid Retinal Vessels Segmentation Model Combining The Latest CNN and MLPs. 405-413 - Liting Li, Yueheng Sun, Tianpeng Li, Minglai Shao:
Robust Few-Shot Graph Anomaly Detection via Graph Coarsening. 414-429 - Ye Li, Mei Wang, Jianwen Su:
An Evaluation Metric for Prediction Stability with Imprecise Data. 430-441 - Haorong Li, Zihao Chen, Jingtao Zhou, Shuangyin Li:
Reducing the Teacher-Student Gap via Elastic Student. 442-453
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