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ORCIDACM Transactions on Knowledge Discovery from Data, Volume 19
Volume 19, Number 1, January 2025
- Guangqian Yang
, Lei Zhang, Yi Liu, Hongtao Xie, Zhendong Mao:
Exploiting Pre-Trained Language Models for Black-Box Attack against Knowledge Graph Embeddings. 1:1-1:14 - Xiao Yu, Hui Liu, Yan Zhang, Yuxiu Lin, Caiming Zhang:
Hubness-Enabled Clustering and Recovery for Large-Scale Incomplete Multi-View Data. 2:1-2:23 - Omer David Harel, Robert Moskovitch:
STORM: A MapReduce Framework for Symbolic Time Intervals Series Classification. 3:1-3:54 - Fatang Lei, Chao Zhang, Huaxiong Li, Yang Gao, Chunlin Chen:
Label Distribution Guided Hashing for Cross-Modal Retrieval. 4:1-4:23 - Zhiwen Zhang, Hongjun Wang, Zipei Fan, Xuan Song, Ryosuke Shibasaki:
Assessing the Spatial-Temporal Causal Impact of COVID-19-Related Policies on Epidemic Spread. 5:1-5:19 - Hanwen Hu, Shiyou Qian, Dingyu Yang, Jian Cao, Guangtao Xue:
Iterative Time Series Imputation by Maintaining Dependency Consistency. 6:1-6:24 - Qingyang Mao, Zhi Li, Qi Liu, Likang Wu, Hefu Zhang, Enhong Chen:
Promoting Machine Abilities of Discovering and Utilizing Knowledge in a Unified Zero-Shot Learning Paradigm. 7:1-7:26 - Chengyuan Mai, Tianchi Liao, Chuan Chen, Zibin Zheng:
FGTL: Federated Graph Transfer Learning for Node Classification. 8:1-8:20 - Zhaolong Ling, Bo Li, Yiwen Zhang, Peng Zhou, Xingyu Wu, Yuee Huang, Kui Yu, Xindong Wu:
Causal Discovery Using Weight-Based Conditional Independence Test. 9:1-9:24 - Bing He, Yibo Hu, Yeon-Chang Lee, Soyoung Oh, Gaurav Verma, Srijan Kumar:
A Survey on the Role of Crowds in Combating Online Misinformation: Annotators, Evaluators, and Creators. 10:1-10:30 - Donghui Chen, Ling Chen, Zongjiang Shang, Youdong Zhang, Bo Wen, Chenghu Yang:
Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting. 11:1-11:23 - Hao Zhang, Ting-Zhu Huang, Xi-Le Zhao, Shuqin Zhang, Jin-Yu Xie, Tai-Xiang Jiang, Michael K. Ng:
Learnable Transform-Assisted Tensor Decomposition for Spatio-Irregular Multidimensional Data Recovery. 12:1-12:23 - Weichao Liang, Guangliang Gao, Lei Chen, Youquan Wang:
Partial Multi-Label Learning via Exploiting Instance and Label Correlations. 13:1-13:22 - Zhixiao Wang, Jiayu Zhao, Chengcheng Sun, Xiaobin Rui, Philip S. Yu:
A General Concave Fairness Framework for Influence Maximization Based on Poverty Reward. 14:1-14:23 - Haoqiang Liu, Weikang Su, Tong Li, Wenzhen Huang, Yong Li:
Digital Twin Enhanced Multi-Agent Reinforcement Learning for Large-Scale Mobile Network Coverage Optimization. 15:1-15:23 - Bijay Prasad Jaysawal, Jen-Wei Huang:
SOHUPDS+: An Efficient One-phase Algorithm for Mining High Utility Patterns over a Data Stream. 16:1-16:32 - Jianwen Sun, Shangheng Du, Jianpeng Zhou, Xin Yuan, Xiaoxuan Shen, Ruxia Liang:
Question Embedding on Weighted Heterogeneous Information Network for Knowledge Tracing. 17:1-17:28 - Zhihao Guan, Jia-Qi Yang, Yang Yang, Hengshu Zhu, Wenjie Li, Hui Xiong:
JobFormer: Skill-Aware Job Recommendation with Semantic-Enhanced Transformer. 18:1-18:20 - Xiaobin Hong, Jiangyi Hu, Taishan Xu, Xiancheng Ren, Feng Wu, Xiangkai Ma, Wenzhong Li:
MagNet: Multilevel Dynamic Wavelet Graph Neural Network for Multivariate Time Series Classification. 19:1-19:22 - Yuchen Wu, Huandong Wang, Changzheng Gao, Depeng Jin, Yong Li:
GeoGail: A Model-Based Imitation Learning Framework for Human Trajectory Synthesizing. 20:1-20:23 - Jun-Yi Hang, Min-Ling Zhang:
Dual Perspective of Label-Specific Feature Learning for Multi-Label Classification. 21:1-21:30 - Yiwen Song, Jingtao Ding, Jian Yuan, Qingmin Liao, Yong Li:
Controllable Human Trajectory Generation Using Profile-Guided Latent Diffusion. 22:1-22:25 - Jiong Zhu, Aishwarya Reganti, Edward W. Huang, Charles Dickens, Nikhil Rao, Karthik Subbian, Danai Koutra:
Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation. 23:1-23:26 - Kaijun Liu, Sijie Ruan, Cheng Long, Liang Yu:
Modeling On-road Trajectories with Multi-task Learning. 24:1-24:26 - Kun He, Xiaodong Xin, Jialu Bao, Meng Wang, Bart Selman, John E. Hopcroft:
Structure Amplification on Multi-layer Stochastic Block Models. 25:1-25:26 - Yalan Qin, Nan Pu, Hanzhou Wu, Nicu Sebe:
Margin-aware Noise-robust Contrastive Learning for Partially View-aligned Problem. 26:1-26:20 - Ruicheng Liang, Yuanchun Jiang, Feida Zhu, Ling Cheng, Huiwen Liu:
Defending Federated Recommender Systems against Untargeted Attacks: A Contribution-Aware Robust Aggregation Scheme. 27:1-27:28
Volume 19, Number 2, February 2025
- Soner Aydin, Sinan Yildirim:
Bayesian Frequency Estimation under Local Differential Privacy with an Adaptive Randomized Response Mechanism. 28:1-28:40 - Zimu Wang, Hao Zou, Jiashuo Liu, Jiayun Wu, Pengfei Tian, Yue He, Peng Cui:
AdaptSel: Adaptive Selection of Biased and Debiased Recommendation Models for Varying Test Environments. 29:1-29:39 - Qiqi Cai, Jian Cao, Yirong Chen, Shiyou Qian, Liangxiao Yuan, Jie Wang:
PREFER: A Pre-trained Model Recommendation Framework for Edge Computing Enabled Traffic Flow Prediction. 30:1-30:26 - Qiang He, Zelin Zhang, Tingting Bi, Hui Fang, Xiushuang Yi, Keping Yu:
Adaptive Rumor Suppression on Social Networks: A Multi-Round Hybrid Approach. 31:1-31:24 - Zhengyang Mao, Wei Ju, Siyu Yi, Yifan Wang, Zhiping Xiao, Qingqing Long, Nan Yin, Xinwang Liu, Ming Zhang:
Learning Knowledge-diverse Experts for Long-tailed Graph Classification. 32:1-32:24 - Haisong Xia, Wanyue Xu, Zuobai Zhang, Zhongzhi Zhang:
Means of Hitting Times for Random Walks on Graphs: Connections, Computation, and Optimization. 33:1-33:35 - Shimin Di, Yongqi Zhang, Quanming Yao, Xiaofang Zhou, Lei Chen:
Efficient Latent-based Scoring Function Search for N-ary Relational Knowledge Bases. 34:1-34:26 - Arya Hadizadeh Moghaddam, Mohsen Nayebi Kerdabadi, Bin Liu, Mei Liu, Zijun Yao:
Discovering Time-aware Hidden Dependencies with Personalized Graphical Structure in Electronic Health Records. 35:1-35:21 - Huan Wang, Yu Teng, Lingsong Qin, Xuan Guo, Po Hu:
A Multiple Attention Layer-shareable Method for Link Prediction in Multilayer Networks. 36:1-36:22 - Yingxue Zhang, Yanhua Li, Xun Zhou, Zhenming Liu, Jun Luo:
C3-GAN+: Complex-Condition-Controlled Generative Adversarial Networks with Enhanced Embedding. 37:1-37:21 - Hanwen Hu, Zhangchi Han, Shiyou Qian, Dingyu Yang, Jian Cao, Guangtao Xue:
Pattern-oriented Attention Mechanism for Multivariate Time Series Forecasting. 38:1-38:26
- Wenqi Fan, Shu Zhao, Jiliang Tang:
Introduction for the Special Issue on Trustworthy Artificial Intelligence. 39:1-39:6 - Zhihao Hu, Yiran Xu, Mengnan Du, Jindong Gu, Xinmei Tian, Fengxiang He:
Boosting Fair Classifier Generalization through Adaptive Priority Reweighing. 40:1-40:26 - Hengyuan Zhang, Zitao Liu, Chenming Shang, Dawei Li, Yong Jiang:
A Question-centric Multi-experts Contrastive Learning Framework for Improving the Accuracy and Interpretability of Deep Sequential Knowledge Tracing Models. 41:1-41:25 - Yao Rong, Guanchu Wang, Qizhang Feng, Ninghao Liu, Zirui Liu, Enkelejda Kasneci, Xia Hu:
Efficient GNN Explanation via Learning Removal-based Attribution. 42:1-42:23 - Sihang Li, Yanchen Luo, An Zhang, Xiang Wang, Longfei Li, Jun Zhou, Tat-Seng Chua:
Self-attentive Rationalization for Interpretable Graph Contrastive Learning. 43:1-43:21 - Guo Lin, Yongfeng Zhang:
Fuzzy Neural Logic Reasoning for Robust Classification. 44:1-44:29 - Enyan Dai, Suhang Wang:
Towards Prototype-Based Self-Explainable Graph Neural Network. 45:1-45:20 - Yu-Neng Chuang, Kwei-Herng Lai, Ruixiang Tang, Mengnan Du, Chia-Yuan Chang, Na Zou, Xia Hu:
Fair-RGNN: Mitigating Relational Bias on Knowledge Graphs. 46:1-46:18 - Yuxi Huang, Huandong Wang, Guanghua Liu, Yong Li, Tao Jiang:
NeuralCODE: Neural Compartmental Ordinary Differential Equations Model with AutoML for Interpretable Epidemic Forecasting. 47:1-47:18 - Fulan Qian, Yuanjun Zou, Mengyao Xu, Xuejun Zhang, Chonghao Zhang, Chenchu Xu, Hai Chen:
A Comprehensive Understanding of the Impact of Data Augmentation on the Transferability of 3D Adversarial Examples. 48:1-48:41 - Meng Xiao, Min Wu, Ziyue Qiao, Yanjie Fu, Zhiyuan Ning, Yi Du, Yuanchun Zhou:
Interdisciplinary Fairness in Imbalanced Research Proposal Topic Inference: A Hierarchical Transformer-based Method with Selective Interpolation. 49:1-49:21 - Li Ma, Yongchao Liu, Xiaofeng Gao, Peng Zhang, Chuntao Hong:
Building Robust and Trustworthy HGNN Models: A Learnable Threshold Approach for Node Classification. 50:1-50:17 - Yongduo Sui, Shuyao Wang, Jie Sun, Zhiyuan Liu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He:
A Simple Data Augmentation for Graph Classification: A Perspective of Equivariance and Invariance. 51:1-51:24 - Mingyuan Fan, Cen Chen, Chengyu Wang, Jun Huang:
Exploiting Pre-Trained Models and Low-Frequency Preference for Cost-Effective Transfer-based Attack. 52:1-52:18 - Haochun Wang, Sendong Zhao, Zewen Qiang, Zijian Li, Chi Liu, Nuwa Xi, Yanrui Du, Bing Qin, Ting Liu:
Knowledge-tuning Large Language Models with Structured Medical Knowledge Bases for Trustworthy Response Generation in Chinese. 53:1-53:17 - Peng Cui, Zhijie Deng, Wenbo Hu, Jun Zhu:
SDE-HNN: Accurate and Well-Calibrated Forecasting Using Stochastic Differential Equations. 54:1-54:23
Volume 19, Number 3, April 2025
- Xueyan Liu, Wenzhuo Song, Katarzyna Musial, Yang Li, Xuehua Zhao, Bo Yang:
Stochastic Block Models for Complex Network Analysis: A Survey. 55:1-55:35 - Mengzhuo Guo, Qingpeng Zhang, Daniel Dajun Zeng:
An Interpretable Deep Learning-based Model for Decision-making through Piecewise Linear Approximation. 56:1-56:35 - Yongkang Li, Zipei Fan, Xuan Song:
Heterogeneous Hyperbolic Hypergraph Neural Network for Friend Recommendation in Location-based Social Networks. 57:1-57:29 - Dezhong Yao, Sanmu Li, Zhiwei Wang, Peilin Zhao, Gang Wu, Chen Yu, Hai Jin:
Efficient Distributed Sparse Relative Similarity Learning. 58:1-58:27 - Yibo Gao, Zhen Liu, Xinxin Yang, Sibo Lu, Yafan Yuan:
Disentangled Multi-Graph Convolution for Cross-Domain Recommendation. 59:1-59:28 - Yuanhang Shao, Xiuwen Liu:
Nonlinear Correct and Smooth for Graph-Based Semi-Supervised Learning. 60:1-60:32 - Huan Zhang, Liangxiao Jiang, Wenjun Zhang, Geoffrey I. Webb:
Dual-View Learning from Crowds. 61:1-61:21 - Peng Lin, Martin Neil, Norman E. Fenton:
Stacking Factorizing Partitioned Expressions in Hybrid Bayesian Network Models. 62:1-62:28 - Sisi Wang, Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li:
Fuzzy Weighted Principal Component Analysis for Anomaly Detection. 63:1-63:22 - Mustafa Abdallah, Ryan A. Rossi, Kanak Mahadik, Sungchul Kim, Handong Zhao, Saurabh Bagchi:
Evaluation-free Time-series Forecasting Model Selection via Meta-learning. 64:1-64:41 - Peng Zhou, Qi Wang, Yunyun Zhang, Zhaolong Ling, Shu Zhao, Xindong Wu:
Online Stable Streaming Feature Selection via Feature Aggregation. 65:1-65:23 - Jayanta Paul, Siddhartha Mallick, Abhijit Mitra, Anuska Roy, Jaya Sil:
Multi-modal Twitter Data Analysis for Identifying Offensive Posts Using a Deep Cross-Attention-based Transformer Framework. 66:1-66:30 - Paiheng Xu, Yuhang Zhou, Bang An, Wei Ai, Furong Huang:
GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint. 67:1-67:22 - Teo Susnjak, Peter Hwang, Napoleon H. Reyes, Andre L. C. Barczak, Timothy R. McIntosh, Surangika Ranathunga:
Automating Research Synthesis with Domain-Specific Large Language Model Fine-Tuning. 68:1-68:39 - Chenyang Wang, Ling Luo, Uwe Aickelin:
Time Series Classification with Elasticity Using Augmented Path Signatures. 69:1-69:32 - Xiao Gu, Ling Jian, Chongzhi Rao, Zhaohui Bu, Xianggang Cheng:
Together Is Better: Knowledge-aware Model with Resume Fusion for Online Job Recommendation. 70:1-70:15 - Víctor Gallego-Fontenla, Pedro Gamallo-Fernandez, Juan Carlos Vidal, Manuel Lama:
Gradual Drift Detection in Process Models Using Conformance Metrics. 71:1-71:40 - Mingwei Lin, Hengshuo Yang, Xiuqin Xu, Ling Lin, Zeshui Xu, Xin Luo:
Momentum-Accelerated and Biased Unconstrained Non-Negative Latent Factor Model for Handling High-Dimensional and Incomplete Data. 72:1-72:25 - Xuechun Jing, Fuyuan Cao, Kui Yu, Jiye Liang:
CM-CaFE: A Clustering Method with Causality-based Feature Embedding. 73:1-73:23 - Yu Zhu, Ou Wu, Fengguang Su:
Subclass-wise Logit Perturbation for Multi-label Learning. 74:1-74:40 - Jian Ying Liu, Chaowei Zhang, Min Zhang, Xiao Qin, Jifu Zhang:
Similarity Metrics: Chebyshev Coulomb Force and Resultant Force for High-Dimensional Data. 75:1-75:25 - Yannian Kou, Qiuqiang Lin, Chuanhou Gao:
ORIC: Feature Interaction Detection through Online Random Interaction Chains for Click-Through Rate Prediction. 76:1-76:31 - Xiaolin Han, Yikun Zhang, Chenhao Ma, Xuequn Shang, Reynold Cheng, Tobias Grubenmann, Xiaodong Li:
Hypergraph-Enhanced Multi-Granularity Stochastic Weight Completion in Sparse Road Networks. 77:1-77:23 - Xinjian Luo, Xianglong Zhang:
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning. 78:1-78:20 - Xiangfei Fang, Chengying Huan, Heng Zhang, Yongchao Liu, Shaonan Ma, Yanjun Wu, Chen Zhao:
OTM: Efficient k-Order-Based Core Maintenance in Large-Scale Dynamic Hypergraphs. 79:1-79:33
Volume 19, Number 4, 2025
- Yang Li, Di Wang, José M. F. Moura:
Forecasting Graph-Based Time-Dependent Data with Graph Sequence Attention. 1-26 - Fa-You Chen, Yun-Jui Hsu, Chia-Hsun Lu, Hong-Han Shuai, Lo-Yao Yeh, Chih-Ya Shen:
Compressing Deep Neural Networks with Goal-Specific Pruning and Self-Distillation. 1-27 - Tianchun Wang, Dongsheng Luo, Wei Cheng, Haifeng Chen, Xiang Zhang:
DyExplainer: Self-explainable Dynamic Graph Neural Network with Sparse Attentions. 1-21 - Congcong Chen, Lifei Wei, Jintao Xie, Yang Shi:
Privacy-Preserving Machine Learning Based on Cryptography: A Survey. 1-33 - Dongjie Li, Dong Li, Guang Lian:
Representation Learning Based on Ordinary Differential Equations for Dynamic Networks. 1-23 - Zhanyu Liu, Guanjie Zheng, Yanwei Yu:
Multi-scale Traffic Pattern Bank for Cross-city Few-shot Traffic Forecasting. 1-24 - Minh Duc Nguyen, Viet Cuong Ta:
Temporal Structural Preserving with Subtree Attention in Dynamic Graph Transformers. 1-24 - Paolo Pellizzoni, Andrea Pietracaprina, Geppino Pucci:
Fully Dynamic Clustering and Diversity Maximization in Doubling Metrics. 1-45 - Yaling Zhao, Lei Tang, Yunji Liang, Zeyu He, Junchi Ma:
Optimizing Matching for On-Demand Ride-Pooling with Stochastic Day-to-Day Dynamics. 1-29 - Xiuqin Xu, Mingwei Lin, Zeshui Xu, Xin Luo:
Attention-Mechanism-Based Neural Latent-Factorization-of-Tensors Model. 1-27 - Zefang Zong, Tao Feng, Jingwei Wang, Tong Xia, Yong Li:
Deep Reinforcement Learning for Demand-Driven Services in Logistics and Transportation Systems: A Survey. 1-42 - Yan Li, Zhulin Wang, Jing Liu, Lei Guo, Philippe Fournier-Viger, Youxi Wu, Xindong Wu:
Mining Repetitive Negative Sequential Patterns with Gap Constraints. 1-29 - Hao Yan, Senzhang Wang, Chaozhuo Li, Jun Yin, Philip S. Yu, Jianxin Wang:
Have Our Cake and Eat It: Augmentation Diversity and Semantic Consistency Balanced Graph Contrastive Learning. 1-25 - Hongbin Xia, Xiangzhong Meng, Yuan Liu:
Non-Parallel Story Author-Style Transfer with Disentangled Representation Learning. 1-26
Volume 19, Number 5, 2025
- Pongsakorn Jirachanchaisiri, Saranya Maneeroj, Atsuhiro Takasu:
COLANet: Cross-Domain Recommender Systems with Latent Overlapping Items on Graph Neural Networks. 1-33 - Hongjia Xu, Liangliang Zhang, Yao Ma, Sheng Zhou, Zhuonan Zheng, Jiajun Bu:
Learning to Reduce the Scale of Large Graphs: A Comprehensive Survey. 1-25 - Yuyan Ai, Chaoqun Li, Liangxiao Jiang:
Intent-aware Recommendation Based on Principal Component Analysis. 1-21 - Shubham Gupta, Suman Kundu:
Communities in Streaming Graphs: Small Space Data Structure, Benchmark Data Generation, and Linear Algorithm. 1-24 - Lanling Xu, Junjie Zhang, Bingqian Li, Jinpeng Wang, Sheng Chen, Wayne Xin Zhao, Ji-Rong Wen:
Tapping the Potential of Large Language Models as Recommender Systems: A Comprehensive Framework and Empirical Analysis. 1-51 - Xiulin Zheng, Pei-Pei Li, Zan Zhang, Jia Wu, Xindong Wu:
A Relation-Constraint Link Prediction Model for Dynamic Knowledge Graphs with Entity Drift. 1-38 - Lianyu Hu, Mudi Jiang, Yan Liu, Quan Zou, Zengyou He:
Clustering Categorical Data via Multiple Hypothesis Testing. 1-31 - Arash Mozhdehi, Yunli Wang, Sun Sun, Xin Wang:
SED2AM: Solving Multi-Trip Time-Dependent Vehicle Routing Problem Using Deep Reinforcement Learning. 1-33 - Dong Li, Aijia Zhang, Huan Xiong, Biqing Qi, Junqi Gao:
FDphormer: Beyond Homophily with Feature-Difference Position Encoding. 1-19 - Liming Xu, Yongheng Wang, Chunlin He, Quan Tang, Xianhua Zeng, Jiancheng Lv:
Deep Disease Label-guided Graph Convolutional Network for Medical Report Generation. 1-23 - Chun-Yan Sang, Ming Gong, Shigen Liao, Wei Zhou:
MA-GCL4SR: Improving Graph Contrastive Learning-Based Sequential Recommendation with Model Augmentation. 1-21 - Moli Lu, Linhao Luo, Xiaofeng Zhang:
Beyond Static Boundaries: Unraveling Temporal Overlapping Communities with Information Bottleneck Guidance. 1-25 - Fenglin Liu, Xuancheng Ren, Guangxiang Zhao, Chenyu You, Sherry Ma, Xian Wu, Wei Fan, Xu Sun:
Rethinking Natural Language Generation with Layer-Wise Multi-View Decoding. 1-25 - Giovanni Micale, Antonio Di Maria, Roberto Grasso, Vincenzo Bonnici, Alfredo Ferro, Dennis Shasha, Rosalba Giugno, Alfredo Pulvirenti:
MultiGraphMatch: A Subgraph Matching Algorithm for Multigraphs. 1-36 - Shamima Hossain, Christos Faloutsos, Boris Baer, Hyoseung Kim, Vassilis J. Tsotras:
Principled Mining, Forecasting, and Monitoring of Honeybee Time Series with EBV+. 1-30
Volume 19, Number 6, 2025
- Jin-Jie Qiu, Shengda Zhuo, Philip S. Yu, Chang-Dong Wang, Shuqiang Huang:
Online Learning for Noisy Labeled Streams. 1-29 - Rui Wang, Yanan Wang, Ziang Li, Haitao Cheng, Guozi Sun:
Distributed Keyword-guided Topic Model with Lexical Knowledge Supervision. 1-19 - Zhaodu Zhang, Yue Chao, Xuejun Ma:
Robust Distributed Estimation for Modal Regression under Least Squares Approximation. 1-21 - Jiadong Feng, Wei Li, Suhuang Wu, Zhao Wei, Yong Xu, Juhong Wang, Hui Li:
Deep Code Search with Naming-Agnostic Contrastive Multi-View Learning. 1-26 - Kai Ming Ting, Zhong Zhuang, Guansong Pang, Zongyou Liu, Tianrun Liang, Qiuran Zhao:
What Are Anomalies in a Network? 1-34 - Lucas Potin, Rosa Figueiredo, Vincent Labatut, Christine Largeron:
Pattern-Based Graph Classification: Comparison of Quality Measures and Importance of Preprocessing. 1-49 - Yue Guan, Yumei He, Ni Huang, Xunhua Guo, Guoqing Chen:
Mining Linguistic Styles in Bilateral Matching: A Contrastive Learning Approach to Reciprocal Recommendation. 1-25 - Zimu Wang, Jiashuo Liu, Hao Zou, Xingxuan Zhang, Yue He, Dongxu Liang, Peng Cui:
Exploring and Exploiting Data Heterogeneity in Recommendation. 1-34 - Wei Guan, Jian Cao, Haiyan Zhao, Yang Gu, Shiyou Qian:
FeadSeq: A Personalized Federated Anomaly Detection Framework for Discrete Event Sequences. 1-26 - Mario Villaizán-Vallelado, Matteo Salvatori, Carlos Segura, Ioannis Arapakis:
Diffusion Models for Tabular Data Imputation and Synthetic Data Generation. 1-32 - Muhammad S. T. Alfas, Manoj Kumar, Shaurya Shriyam, Sandeep Kumar:
An Efficient Framework for Epidemiological Parameter Estimation via Graph Reduction and Graph Neural Networks. 1-29 - Yufei Jin, Xingquan Zhu:
A Systematic Study and Analysis of Graph Neural Networks under Noise. 1-20 - Shangyang Li, Jiayan Guo:
Subgraph Federated Learning with Information Bottleneck Constrained Generative Learning. 1-23 - Budhitama Subagdja, D. Shanthoshigaa, Ah-Hwee Tan:
DisambiguART: A Neural-based Inference Model for Knowledge Graph Disambiguation. 1-29
Volume 19, Number 7, August 2025
- Gengsen Huang, Wensheng Gan, Philip S. Yu:
Towards Sequence Utility Maximization under Utility Occupancy Measure. 126:1-126:27 - Shichao Zhang, Penghui Xi, Mengqi Jiang, Guixian Zhang, Debo Cheng:
Latent Representation Learning for Attributed Graph Anomaly Detection. 127:1-127:22 - Ece Alptekin, Berkay Kemal Balioglu, Mehmet Emre Gursoy:
Hierarchical Spatial Decompositions under Local Differential Privacy. 128:1-128:37 - Fulan Qian, Wenbin Chen, Hai Chen, Yan Cui, Shu Zhao, Yanping Zhang:
Understanding the Robustness of Deep Recommendation under Adversarial Attacks. 129:1-129:46 - Jianping Zhou, Bin Lu, Zhanyu Liu, Siyu Pan, Xuejun Feng, Hua Wei, Guanjie Zheng, Xinbing Wang, Chenghu Zhou:
MagiNet: Mask-Aware Graph Imputation Network for Incomplete Traffic Data. 130:1-130:20 - Zhen Tao, Dinghao Xi, Zhiyu Li, Liumin Tang, Wei Xu:
CAT-LLM: Style-enhanced Large Language Models with Text Style Definition for Chinese Article-style Transfer. 131:1-131:33 - Haoran Zong, Xiao Zhang, Ruichen Li, Jianhui Duan, Derun Zou, Wenzhong Li:
Convergence-Guaranteed Federated Learning through Gradient Trajectory Smoothing with Triple-Objective Decomposition. 132:1-132:31 - Jian Chen, Yile Chen, Zeyi Wen, Yawen Chen, Jin Huang:
Towards Recommendation on Good Quality Data Science Solutions. 133:1-133:19 - Haifeng Sun, Yuanyi Wang, Han Li, Wei Tang, Zirui Zhuang, Qi Qi, Jingyu Wang:
Understanding and Guiding Weakly Supervised Entity Alignment with Potential Isomorphism Propagation. 134:1-134:28 - Xiya Bu, Yu Liu:
Knowledge Graph Fine-grained Modeling Network with Contrastive Learning for Recommendation. 135:1-135:18 - Naaek Chinpattanakarn, Chainarong Amornbunchornvej:
Framework for Variable-Lag Motif Following Relation Inference in Time Series Using Matrix Profile Analysis. 136:1-136:24 - Bohao Li, Bowen Du, Junchen Ye:
PRIME: Pretraining for Patient Condition Representation with Irregular Multimodal Electronic Health Records. 137:1-137:39 - Huiting Liu, Wei Zhang, Pei-Pei Li, Peng Zhao, Xindong Wu:
Causal Meta-learning with Multi-view Graphs for Cold-start Recommendation. 138:1-138:29 - Mohna Chakraborty, Adithya Kulkarni, Qi Li:
Weakly Supervised Open-Domain Aspect-Based Sentiment Analysis. 139:1-139:29 - Hanchen Yang, Jiannong Cao, Wengen Li, Shuyu Wang, Hui Li, Jihong Guan, Shuigeng Zhou:
Spatial-Temporal Data Mining for Ocean Science: Data, Methodologies and Opportunities. 140:1-140:47 - Hao Liu, Dong Li, Bing Zeng, Wei Liang, Dongjie Li:
Graph Self-attention Mechanism for Interpretable Multi-hop Knowledge Graph Link Prediction. 141:1-141:22 - Xingyu Zhao, Yuexuan An, Ning Xu, Lei Qi, Xin Geng:
Interactive Fusion Label Enhancement for Multi-Label Learning. 142:1-142:23 - Jiaqi Wang, Wengen Li, Yulou Shu, Jihong Guan, Yichao Zhang, Shuigeng Zhou:
Raker: A Relation-Aware Knowledge Reasoning Model for Inductive Relation Prediction. 143:1-143:20
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