Regular papers
| Paper ID | Title | Author Names | Keywords |
|---|---|---|---|
| DM211 | Generating Realistic Tabular Data with Large Language Model | Dang Nguyen, Sunil Gupta, Kien Do, Thin Nguyen, and Svetha Venkatesh | Classification, Generative model, Large language model (LLM), Tabular data generation, Realistic tabular samples |
| DM216 | Graph Community Augmentation with GMM-based Modeling in Latent Space | Shintaro Fukushima and Kenji Yamanishi | Community Augmentation, Extrapolation, Generative Model, Graph Generation, Minimum Description Length Principle |
| DM233 | Solving Combinatorial Optimization Problem over Graph through QUBO Transformation and Deep Reinforcement Learning | Tianle Pu, Chao Chen, Li Zeng, Shixuan Liu, Rui Sun, and Changjun Fan | Combinatorial Optimization, Quadratic Unconstrained Binary Optimization, Reinforcement Learning, Graph Transformer |
| DM245 | HyperTime: A Dynamic Hypergraph Approach for Time Series Classification | Raneen Younis and Zahra Ahmadi | Time series classification, Dynamic hypergraph, Graph neural networks |
| DM254 | Towards Efficient Ridesharing via Order-Vehicle Pre-Matching Using Attention Mechanism | Zhidan Liu, Jinye Lin, Zhiyu Xia, Chao Chen, and Kaishun Wu | Ridesharing, Order-vehicle pre-matching, Self-attention mechanism, Spatial-temporal |
| DM270 | DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning | Kangyang Luo, Shuai Wang, Yexuan Fu, Renrong Shao, Xiang Li, Yunshi Lan, Ming Gao, and Jinlong Shu | One-shot Federated Learning, Data-free knowledge distillation, Data heterogeneity, Model heterogeneity |
| DM277 | Transitivity-Encoded Graph Attention Networks for Complementary Item Recommendations | Jin Shang, Yang Jiao, Chenghuan Guo, Minghao Sun, Yan Gao, Jia Liu, Michinari Momma, Itetsu Taru, and Yi Sun | complementary recommendation, graph neural networks, graph attention networks, self-supervised learning |
| DM288 | SR-PredictAO: Session-based Recommendation with High-Capability Predictor Add-On | Ruida WANG, Raymond Chi-Wing Wong, and Weile TAN | session-based recommendation, recommender system, neural decision forest, tree-based method |
| DM301 | Improving Time Series Encoding with Noise-Aware Self-Supervised Learning and an Efficient Encoder | Duy Nguyen Anh, Trang Tran, Hieu Pham Huy, Le Nguyen Phi, and Lam Nguyen Minh | Time series representation learning, Noise-resiliency training strategy, Inception |
| DM306 | Efficient Network Embedding by Approximate Equitable Partitions | Giuseppe Squillace, Mirco Tribastone, Max Tschaikowski, and Andrea Vandin | Equitable partitions, network embedding, backward equivalence, structural equivalence |
| DM315 | Hierarchical Explanations for Text Classification Models: Fast and Effective | Zhenyu Nie, Zheng Xiao, Huizhang Luo, Xuan Liu, and Anthony Theodore Chronopoulos | Hierarchical interpretation, Explanation efficiency, Word interactions, Text classification |
| DM319 | ADOD: Adaptive Density Outlier Detection | Li Qian, Jing Qian, Xin Sun, Wengang Guo, and Christian Böhm | Outlier Detection, Unsupervised Learning, Adaptive Density, Mutual Neighbors Graph |
| DM322 | Adaptive Graph Neural Networks for Cold-start Multimedia Recommendation | Zhen Li, Jibin Wang, Zhuo Chen, Kun Wu, Yuanzhen Wei, and Hai Huang | Multimedia Recommendation, Graph Neural Network, Social Network, Multimodal |
| DM323 | Graph Contrastive Learning with Adversarial Structure Refinement (GCL-ASR) | Jiangwen Chen, Kou Guang, Qiyang Li, and Tan Hao | GNN, GCL, GANs, Data mining |
| DM327 | Adaptive Loss-ware Modulation for Multimedia Retrieval | Jian Zhu, Yu Cui, Zeyi Sun, Yuyang Dai, Xi Wang, Lei Liu, Cheng Luo, and Li-Rong Dai | Multi-view Hash, Gradient Modulation, Multi-modal Hash, Multimedia Retrieval, Image Retrieval. |
| DM331 | Enhancing Embeddings Quality with Stacked Gate for Click-Through Rate Prediction | Caihong Mu, Yunfei Fang, Jialiang Zhou, and Yi Liu | CTR Prediction, AutoML, Neural Architecture Search, Recommendation |
| DM337 | Towards Cross-domain Few-shot Graph Anomaly Detection | Jiazhen Chen, Sichao Fu, Zhibin Zhang, Zheng Ma, Mingbin Feng, Tony Wirjanto, and Qinmu Peng | Graph Anomaly Detection, Graph Neural Network, Few-shot Learning, Domain Adaptation, Prompt Learning |
| DM359 | Debunking Fake News in Online Social Networks without Text Analysis | Xing Su, Jian Yang, Jia Wu, and Zitai Qiu | Fake News Detection, Hypergraph, High-order Relations, Text-independent |
| DM363 | Scalable Order-Preserving Pattern Mining | Ling Li, Wiktor Zuba, Grigorios Loukides, Solon Pissis, and Maria Matsangidou | frequent pattern mining, order-preserving, string algorithms, indexing |
| DM366 | Designing an attack-defense game: how to increase the robustness of financial transaction models via a competition | Alexey Zaytsev, Alex Natekin, Evgeni Vorsin, Valerii Smirnov, Georgii Smirnov, Oleg Sidorshin, Alexander Senin, Alexander Dudin, Maria Kovaleva, and Dmitry Berestnev | Adversarial attacks, Robustness, Deep learning, Financial data |
| DM367 | Continuous Exact Explanations of Neural Networks | Alice Dethise and Marco Canini | explainable ML, machine learning, post-hoc explanations |
| DM373 | Utilitarian Online Learning from Open-World Soft Sensing | Heng Lian, Yu Huang, Xingquan Zhu, and Yi He | Data Streams, Online Learning, Optimal Rejection, Soft Sensing, Industrial Data Mining |
| DM378 | Probabilistic Matrix Factorization-based Three-stage Label Completion for Crowdsourcing | Boyi Yang, Liangxiao Jiang, and Wenjun Zhang | Crowdsourcing learning, label completion, probabilistic matrix factorization |
| DM383 | Informative Subgraphs Aware Masked Auto-Encoder in Dynamic Graphs | Pengfei Jiao, Xinxun Zhang, Mengzhou Gao, and Tianpeng Li | graph representation learning, dynamic graphs, masked auto-encoder, self-supervised learning |
| DM388 | ELiCiT: Effective and Lightweight Lossy Compression of Tensors | Jihoon Ko, Taehyung Kwon, Jinhong Jung, and Kijung Shin | Matrix Compression, Tensor Compression, Matrix Completion, Neural-network Compression |
| DM393 | LISA: Learning-Integrated Space Partitioning Framework for Traffic Accident Forecasting on Heterogeneous Spatiotemporal Data | Bang An, Xun Zhou, Amin Khezerlou, Nick Street, Jinping Guan, and Jun Luo | Spatialtemporal Data Mining, Traffic Accident Forecasting |
| DM402 | RecCoder: Reformulating Sequential Recommendation as Large Language Model-Based Code Completion | Kai-Huang Lai, Wudong Xi, Xingxing Xing, Wei Wan, Chang-Dong Wang, Min Chen, and Mohsen Guizani | large language model, sequential recommendation |
| DM409 | Scaling Disk Failure Prediction via Multi-Source Stream Mining | Shujie Han, Zirui Ou, Qun Huang, and Patrick P. C. Lee | disk failure prediction, multi-source stream mining, scalability |
| DM410 | Contrastive Learning for Adapting Language Model to Sequential Recommendation | Fei-Yao Liang, Wu-Dong Xi, Xing-Xing Xing, Wei Wan, Chang-Dong Wang, Min Chen, and Mohsen Guizani | sequential recommendation, contrastive learning, large language model |
| DM412 | GQ*: Towards Generalizable Deep Q-Learning for Steiner Tree in Graphs | Wei Huang, Hanchen Wang, Dong Wen, Xuefeng Chen, Wenjie zhang, and Ying Zhang | Steiner Tree, Reinforcement Learning, Graph Neural Networks, A* Search |
| DM413 | HomoMGC: Homophily-enhanced Adaptive Graph Refinement for Multi-view Graph Clustering | Man-Sheng Chen, Xiao-Sha Cai, Chang-Dong Wang, Dong Huang, Min Chen, and Mohsen Guizani | multi-view graph clustering, homophily assumption, heterogeneous edges, adaptive graph refinement, low-rank tensor |
| DM419 | Cross-Store Next-Basket Recommendation | Liangchen Ma, Ya Li, Zifeng Mai, Feiyao Liang, Chang-Dong Wang, Min Chen, and Mohsen Guizani | next-basket recommendation, cross-domain recommendation, graph neural network |
| DM430 | Emotional Synchronization for Audio-Driven Talking-Head Generation | Zhao Zhang, Yan Luo, Zhichao Zuo, Richang Hong, Yi Yang, and Meng Wang | Audio-driven talking-head synthesis, Emotional synchronization, Attention |
| DM436 | High-Fidelity Diffusion Editor for Zero-Shot Text-Guided Video Editing | Yan Luo, Zhichao Zuo, Zhao Zhang, Zhongqiu Zhao, Haijun Zhang, and Richang Hong | Zero-shot video editing, High-fidelity, Diffusion-based generative model, Text-to-video, Spatial-temporal attention. |
| DM438 | Early Fire Detection based on Local Morphological Knowledge Matching | Xinzhi Wang, Mengyue Li, Nengjun Zhu, Jiayan Qian, and Zhanyi Zheng | local morphological knowledge, fire object localization, early fire detection |
| DM442 | GADIN: Generative Adversarial Denoise Imputation Network for Incomplete Data | Dong Li, Zhicong Liu, Mingfeng Hu, Baoyan Song, and Xiaohuan Shan | Missing data, Data imputation, Generative adversarial network, Denoising network |
| DM455 | APOLLO: Differential Private Online Multi-Sensor Data Prediction with Certified Performance | Honghui Xu, Wei Li, Shaoen Wu, Liang Zhao, and Zhipeng Cai | Multi-sensor Data Analysis, Differential Privacy, Correlated Data Privacy |
| DM461 | Combining Self-Supervision and Privileged Information for Representation Learning from Tabular Data | Haoyu Yang, Gyorgy Simon, Michael Steinbach, Genevieve Melton, and Vipin Kumar | Self-Supervised Learning, Privileged Information, Representation Learning, Healthcare |
| DM475 | Align Along Time and Space: A Graph Latent Diffusion Model for Traffic Dynamics Prediction | Yuhang Liu, Yingxue Zhang, Xin Zhang, Yu Yang, Yiqun Xie, Sahar Ghanipoor Machiani, Yanhua Li, and Jun Luo | urban dynamics prediction, latent diffusion models, spatial-temporal data mining |
| DM482 | EEiF: Efficient Isolated Forest with e Branches for Anomaly Detection | Yifan Zhang, Haolong Xiang, Xuyun Zhang, Xiaolong Xu, Wei Fan, Qin Zhang, and Lianyong Qi | Anomaly Detection, FR clustering, Efficient, Parallel Algorithm |
| DM488 | Margin-bounded Confidence Scores for Out-of-Distribution Detection | Lakpa Tamang, Mohamed Reda Bouadjenek, Richard Dazeley, and Sunil Aryal | out-of-distribution, outlier exposure, confidence score, weighted penalty |
| DM510 | Towards Dynamic University Course Timetabling Problem: An Automated Approach Augmented via Reinforcement Learning | Yanan Xiao, XiangLin Li, Lu Jiang, Pengfei Wang, Kaidi Wang, and Na Luo | Course Timetable, Reinforcement Learning |
| DM515 | Fast and Accurate Triangle Counting in Graph Streams Using Predictions | Cristian Boldrin and Fabio Vandin | Triangle Counting, Sampling, Algorithms with Predictions, Graph Stream Mining |
| DM546 | Efficiently Manipulating Structural Graph Clustering Under Jaccard Similarity | Chuanyu Zong, Rui Fang, Meng-xiang Wang, Tao Qiu, and Anzhen Zhang | Structural graph clustering, Jaccard similarity, Manipulation, Incremental computation |
| DM591 | HFGNN: Efficient Graph Neural Networks using Hub-Fringe Structures | Pak Lon Ip, Sheng Hui Zhang, Xue Kai Wei, Tsz Nam Chan, and Leong Hou U | Expressivity, Graph Neural Networks, Hub-Fringe, Hub Labeling |
| DM610 | A Bayesian Hierarchical Model for Orthogonal Tucker Decomposition with Oblivious Tensor Compression | Matthew Pietrosanu, Bei Jiang, and Linglong Kong | Bayes methods, Compressed sensing, Monte Carlo methods, Statistical analysis, Tensors |
| DM611 | Normalizing self-supervised learning for provably reliable Change Point Detection | Alexandra Bazarova, Evgenia Romanenkova, and Alexey Zaytsev | change point detection, self-supervised learning, spectral normalization |
| DM634 | Counterfactual Brain Graph Augmentation Guided Bi-Level Contrastive Learning for Disorder Analysis | Guangwei Dong, Xuexiong Luo, Jing Du, Jia Wu, Shan Xue, Jian Yang, and Amin Beheshti | Counterfactual augmentation, Brain disorder analysis, Graph contrastive learning |
| DM641 | CounterFair: Group Counterfactuals for Bias Detection, Mitigation and Subgroup Identification | Alejandro Kuratomi, Zed Lee, Panayiotis Tsaparas, Guilherme Dinis Junior, Evaggelia Pitoura, Tony Lindgren, and Panagiotis Papapetrou | Counterfactual explanations, Algorithmic fairness, Group counterfactuals, Local explainability |
| DM655 | Financial Risk Assessment via Long-term Payment Behavior Sequence Folding | Yiran Qiao, Yateng Tang, Xiang Ao, Qi Yuan, Ziming Liu, Chen Shen, and Xuehao Zheng | Financial Risk Assessment, Long Sequence Modeling, User Behavior Modeling |
| DM667 | Scalable Graph Classification via Random Walk Fingerprints | Peiyan Li, Honglian Wang, and Christian Böhm | Graph Classification, Feature Extraction, Scalability, Interpretability |
| DM690 | Dual Cross-Stage Partial Learning for Enhanced Object Detection in Dehazed Images | Jinbiao Zhao, Zhao Zhang, Jiahuan Ren, Haijun Zhang, Zhongqiu Zhao, and Meng Wang | Image dehazing, object detection, anchor-free, dual cross stage partial learning |
| DM697 | Resource2Box: Learning To Rank Resources in Distributed Search Using Box Embedding | Ulugbek Ergashev, Geon Lee, Kijung Shin, Eduard Dragut, and Weiyi Meng | Box Embedding, Learning to Rank, Distributed Search |
| DM709 | ChronoCTI: Mining Knowledge Graph of Temporal Relations among Cyberattack Actions | Md Rayhanur Rahman, Brandon Wroblewski, Quinn Matthews, Brantley Morgan, Timothy Menzies, and Laurie Williams | MITRE ATT&CK, Temporal relation, Cyberthreat intelligence, CTI reports, Knowledge graph |
| DM713 | Traffic Pattern Sharing for Federated Traffic Flow Prediction with Personalization | Hang Zhou, Wentao Yu, Sheng Wan, Yongxin Tong, Tianlong Gu, and Chen Gong | spatial-temporal data, traffic flow prediction, personalized federated learning |
| DM717 | Warm-Starting Contextual Bandits under Latent Reward Scaling | Bastian Oetomo, R. Malinga Perera, Renata Borovica-Gajic, and Benjamin I. P. Rubinstein | multi-armed bandits, warm-start, pre-training |
| DM734 | Feature Map Purification for Enhancing Adversarial Robustness of Deep Timeseries Classifiers | Mubarak Abdu-Aguye, Zaigham Zaheer, and Karthik Nandakumar | adversarial robustness, feature maps, purification, timeseries, wavelets |
| DM743 | Adaptive Process-Guided Learning: An Application in Predicting Lake DO Concentrations | Runlong Yu, Chonghao Qiu, Robert Ladwig, Paul Hanson, Yiqun Xie, Yanhua Li, and Xiaowei Jia | physics-guided learning, knowledge integration, adaptive learning, ecosystem modeling |
| DM745 | TROPICAL: Transformer-based Hypergraph Learning for Camouflaged Fraudsters Detection | Venus Haghighi, Behnaz Soltani, Nasrin Shabani, Jia Wu, Yang Zhang, Lina Yao, Quan Z. Sheng, and Jian Yang | Hypergraph Learning, Camouflage, Fraud Detection |
| DM747 | DISCO: A Hierarchical Disentangled Cognitive Diagnosis Framework for Interpretable Job Recommendation | Xiaoshan Yu, Chuan Qin, Qi Zhang, Chen Zhu, Haiping Ma, Xingyi Zhang, and Hengshu Zhu | Online recruitment, job recommendation, cognitive diagnosis, disentangled learning |
| DM760 | MOStream: A Modular and Self-Optimizing Data Stream Clustering Algorithm | Zhengru Wang, Xin Wang, and Shuhao Zhang | data stream clustering, cluster evolution, outlier evolution, dimention changes |
| DM772 | TAN: A Tripartite Alignment Network Enhancing Composed Image Retrieval with Momentum Distillation | Yongquan Wan, Erhe Yang, Cairong Yan, Guobing Zou, and Bofeng Zhang | image retrieval, composed image retrieval, multimodal, knowledge distillation |
| DM776 | PROMIPL:A Probabilistic Generative Model for Multi-Instance Partial-Label Learning | Yin-Fang Yang, Wei Tang, and Min-Ling Zhang | Multi-Instance Partial-Label Learning, Generative Model, Probabilistic Disambiguation, Label Distribution, Variational Bayesian. |
| DM778 | Bi-level User Modeling for Deep Recommender Systems | Yejing Wang, Dong Xu, Xiangyu Zhao, Zhiren Mao, Peng Xiang, Ling Yan, Yao Hu, Zijian Zhang, Xuetao Wei, and Qidong Liu | User Modeling, Deep Recommender Systems, CTR Prediction |
| DM783 | A Novel Shadow Variable Catcher for Addressing Selection Bias in Recommendation Systems | Qingfeng Chen, Boquan Wei, Debo Cheng, Jiuyong Li, Lin Liu, and Shichao Zhang | Recommendation systems, causal inference, selection bias, shadow variables. |
| DM790 | EMIT - Event Based Masked Auto Encoding for Irregular Time Series | Hrishikesh Patel, Ruihong Qiu, Adam Irwin, Shazia Sadiq, and Sen Wang | Irregular time series, Self-supervised learning, Healthcare |
| DM806 | A Learned Approach to Index Algorithm Selection | Chaohong Ma, Xiaohui Yu, Yifan Li, Aishan Maoliniyazi, and Xiaofeng Meng | Algorithm selection, Featurization, Adaptation |
Short papers
| Paper ID | Title | Author Names | Keywords |
|---|---|---|---|
| DM223 | MetaSTC: A Meta Spatio-Temporal Learning Paradigm for Traffic Flow Prediction | Kexin Xu, Zhemeng Yu, Yucen Gao, Songjian Zhang, Jun Fang, Xiaofeng Gao, and Guihai Chen | Spatio-Temporal Data Mining, Meta-Learning, Traffic Flow Prediction, Backbone Agnostic |
| DM227 | Matrix Profile for Anomaly Detection on Multidimensional Time Series | Chin-Chia Michael Yeh, Audrey Der, Uday Singh Saini, Vivian Lai, Yan Zheng, Junpeng Wang, Xin Dai, Zhongfang Zhuang, Yujie Fan, Huiyuan Chen, Prince Aboagye, Liang Wang, Wei Zhang, and Eamonn Keogh | time series, anomaly detection, multidimensionality |
| DM241 | Hi-Gen: Generative Retrieval For Large-Scale Personalized E-commerce Search | YanjingWu Wu, Yinfu Feng, Jian Wang, Wenji Zhou, Yunan Ye, Rong Xiao, and Jun Xiao | Search and Recommendation System, Information Retrieval, Generative Retrieval, Personalization |
| DM259 | 2DXformer: Dual Transformers for Wind Power Forecasting with Dual Exogenous Variables | Yajuan Zhang, Jiahai Jiang, Yule Yan, liang Yang, and ping zhang | wind power forecasting, spatiotemporal forecasting, exogenous variables, variable correlation |
| DM266 | Goal-guided Generative Prompt Injection Attack on Large Language Models | Chong Zhang, Mingyu Jin, Qinkai Yu, Chengzhi Liu, Haochen Xue, and Xiaobo Jin | Prompt Injection, KL-divergence, Robustness, Mahalanobis Distance |
| DM271 | CL4CO: A Curriculum Training Framework for Graph-based Neural Combinatorial Optimization | Yang Liu, Chuan Zhou, Peng Zhang, Zhao Li, Shuai Zhang, Xixun Lin, and Xindong Wu | curriculum learning, combinatorial optimization, graph neural networks |
| DM295 | QUCE: The Minimisation and Quantification of Path-Based Uncertainty for Generative Counterfactual Explanations | Jamie Duell, Monika Seisenberger, Hsuan Fu, and Xiuyi Fan | Counterfactuals, Explainability, Deep Learning, Neural Networks, Interpretability |
| DM320 | A Momentum Contrastive Learning Framework for Query-POI Matching | Yuting Qiang, Jianbin Zheng, Lixia Wu, Haomin Wen, Junhong Lou, and Minhui Deng | cross-modal learning, contrastive learning, query-POI matching |
| DM325 | Generalized Sparse Additive Model with Unknown Link Function | Peipei Yuan, Xinge You, Hong Chen, Xuelin Zhang, and Qinmu Peng | generalized additive models, unknown link function, variable interaction, bilevel optimization, convergence analysis |
| DM326 | SHADE: Deep Density-based Clustering | Anna Beer, Pascal Weber, Lukas Miklautz, Collin Leiber, Walid Durani, Christian Böhm, and Claudia Plant | Clustering, Deep Clustering, Density-based Clustering, DBSCAN |
| DM334 | Interdependency Matters: Graph Alignment for Multivariate Time Series Anomaly Detection | Yuanyi Wang, Haifeng Sun, Chengsen Wang, Mengde Zhu, Wei Tang, Jingyu Wang, Qi Qi, Zirui Zhuang, and Jianxin Liao | multivariate time series, anomaly detection, graph alignment, unsupervised learning |
| DM343 | Exploitation or Exploration Next? User Behavior Decoupling and Emerging Intent Modeling for Next-Item Recommendation | Nengjun Zhu, Lingdan Sun, Xiangfeng Luo, Jian Cao, Qi Zhang, and Xinjiang Lu | Session-based recommendation, Intent modeling, Behavior decoupling, Hypergraph learning, Neighbor retrieval |
| DM371 | Multi-modal Sarcasm Detection via Dual Synergetic Perception Graph Convolutional Networks | Xingjie Zhuang and Zhixin Li | Sarcasm detection, Multi-modal learning, Information fusion, Graph networks, Knowledge embedding |
| DM384 | Exploratory Combinatorial Optimization Problem Solving via Gauge Transformation | Tianle Pu, Changjun Fan, Mutian Shen, Yizhou Lu, Li Zeng, Zohar Nussinov, Chao Chen, and Zhong Liu | Combinatorial Optimization, Gauge Transformation, Graph Neural Network, Reinforcement Learning, MaxCut Problem |
| DM385 | SplitSEE: A Splittable Self-supervised Framework for Single-channel EEG Representation Learning | Rikuto Kotoge, Zheng Chen, Tasuku Kimura, Yasuko Matsubara, Takufumi Yanagisawa, Haruhiko Kishima, and Yasushi Sakurai | EEG, representation learning, self-supervised learning, federated learning |
| DM390 | Accurate and Fast Estimation of Temporal Motifs using Path Sampling | Yunjie Pan, Omkar Bhalerao, C. Seshadhri, and Nishil Talati | temporal graphs, temporal motif mining, approximate algorithms |
| DM394 | DynoGraph: Dynamic Graph Construction for Nonlinear Dimensionality Reduction | Li Qian, Claudia Plant, Yalan Qin, Jing Qian, and Christian Böhm | Dimensionality Reduction, Unsupervised Learning, Adaptive Neighborhood Graph, Dynamic Graph Modification |
| DM414 | Periodic Prompt on Dynamic Heterogeneous Graph for Next Basket Recommendation | Ru-Bin Li, Man-Sheng Chen, Xin-Yu Ding, Chang-Dong Wang, Sihong Xie, Shuangyin Liu, Min Chen, and Mohsen Guizani | graph prompt, graph neural network, next basket recommendation, dynamic and heterogeneous information |
| DM446 | Constructing $\epsilon$-Constrained Sparsified $\beta^s$-Complexes using Space Partitioning Trees | Rohit Singh and Philip Wilsey | Sparsification, Space Partitioning, Persistent Homology, Data Mining |
| DM449 | Channel-Attentive Graph Neural Networks | TuÄŸrul Hasan Karabulut and Ä°nci M. BaytaÅŸ | Deep learning, Graph neural network, Representation learning, Attention |
| DM454 | A Condensed Transition Graph Framework for Zero-shot Link Prediction with Large Language Models | Mingchen Li, Chen Ling, rui Zhang, and Liang Zhao | Zero-Shot Link Prediction, Condensed Transition, Graph, Large Language Models |
| DM462 | Towards Expressive Graph Representations for Graph Neural Networks | Chengsheng Mao, Liang Yao, and Yuan Luo | graph neural network, graph representation, expressive power, injective mapping, set representation. |
| DM467 | Weakly-Supervised Graph Classification with Even a Single Key Subgraph Per Class | Lu Zhang, Chenbo Zhang, Jihong Guan, and Shuigeng Zhou | graph classification, weakly-supervised learning, subgraphs |
| DM483 | Futures Quantitative Investment with Heterogeneous Continual Graph Neural Network | Zhizhong Tan, Min Hu, Bin Liu, and Guosheng Yin | Continual learning, futures price forecasting, graph neural network, spatio-temporal data |
| DM495 | Influence-aware Group Recommendation for Social Media Propagation | Chengkun He, Xiangmin Zhou, Chen Wang, Longbing Cao, Jie Shao, and Zahir Tari | group recommendation, influence propagation |
| DM497 | Multi-Hyperbolic Space-based Heterogeneous Graph Attention Network | Jongmin Park, Seunghoon Han, Jong-Ryul Lee, and Sungsu Lim | heterogeneous graph representation learning, graph neural networks, hyperbolic graph embedding, graph data mining, heterogeneous graph embeding |
| DM517 | DifFaiRec: Generative Fair Recommender with Conditional Diffusion Model | Zhenhao Jiang and Jicong Fan | Recommender System, Group Fairness, Diffusion Model, Counterfactual Module |
| DM559 | FGLBA: Enabling Highly-Effective and Stealthy Backdoor Attack on Federated Graph Learning | Qing Lu, Miao Hu, Di Wu, Yipeng Zhou, Mohsen Guizani, and Quan Z. Sheng | backdoor attack, federated graph learning |
| DM573 | D-Cube : Exploiting Hyper-Features of Diffusion Model for Robust Medical Classification | Minhee Jang, Juheon Son, Thanaporn Viriyasaranon, Junho Kim, and Jang-hwan Choi | Medical Image Classification, Diffusion Models, Feature Selection, Contrastive Learning, Synthetic Data Generation |
| DM580 | Cascading Multimodal Feature Enhanced Contrast Learning for Music Recommendation | Qimeng Yang, Shijia Wang, Da Guo, Dongjin Yu, Qiang Xiao, Dongjing Wang, and Chuanjiang Luo | music recommendation, representation learning, data bias, contrastive learning, multimodal feature |
| DM583 | Enhancing Entity Alignment on Probabilistic Knowledge Graphs | Yunfei Li, Lu Chen, Chengfei Liu, Rui Zhou, and Jianxin Li | Probabilistic Knowledge Graph, Entity Alignment, Probabilistic Graph Neural Network, Markov Chain Monte Carlo, Probabilistic Knowledge Graph Embedding |
| DM604 | AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models | Shuo Liu, Yao Di, Lanting Fang, Zhetao Li, Wenbin Li, Kaiyu Feng, Xiaowen Ji, and Jingping Bi | Dynamic Graphs, Anomaly Detection, Few-Shot Learning, Large Language Models |
| DM605 | SemiFDA: Domain Adaptation in Semi-Supervised Federated Learning | Michele Craighero, Giorgio Rossi, Beatrice Rossi, Diego Carrera, Diego Stucchi, Pasqualina Fragneto, and Giacomo Boracchi | Human Activity Recognition, semi-supervised, domain shift, federated learning, features alignment |
| DM617 | IIFE: Interaction Information Based Automated Feature Engineering | Tom Overman, Diego Klabjan, and Jean Utke | Automated Feature Engineering, Feature Engineering, Automated Data Science |
| DM628 | Unsupervised Domain Adaptation for Action Recognition via Self-Ensembling and Conditional Embedding Alignment | Indrajeet Ghosh, Garvit Chugh, Abu Zaher Md Faridee, and Nirmalya Roy | Unsupervised Domain Adaptation, Conditional Alignment, Wearable-based Action Recognition, Consistency Regularization, Temporal Ensembling |
| DM648 | Survival Analysis with Multiple Noisy Labels | Donna Tjandra and Jenna Wiens | Health Application, Survival Analysis, Time-to-Event Prediction, Noisy Labels, Multiple Labelers |
| DM649 | Controllable Visit Trajectory Generation with Spatiotemporal Constraints | Haowen Lin, John Krumm, Cyrus Shahabi, and Li Xiong | Spatial-temporal systems, Controlled generation |
| DM663 | A Parameter Update Balancing Algorithm for Multi-task Ranking Models in Recommendation Systems | Jun Yuan, Guohao Cai, and Zhenhua Dong | Multi-task Optimization, Recommendation System |
| DM672 | Reducing Unfairness in Distributed Community Detection | Hao Zhang, Malith Jayaweera, Bin Ren, Yanzhi Wang, and Sucheta Soundarajan | big graph data, community detection, big data processing fairness |
| DM681 | Graph Rhythm Network: Beyond Energy Modeling for Deep Graph Neural Networks | Yufei Jin and Xingquan Zhu | Graph rhythm, graph neural network, oversmoothing, graph embedding |
| DM708 | An Explainable Recommender System by Integrating Graph Neural Networks and User Reviews | Sahar Batmani, Parham Moradi, Narges Haidari, and Mahdi Jalili | Recommender System, Explainability, Graph Neural Networks, Temporal Convolution Networks, User Reviews |
| DM726 | ExoTST: Exogenous-Aware Temporal Sequence Transformer for Time Series Prediction | Kshitij Tayal, Arvind Renganathan, Xiaowei Jia, Vipin Kumar, and Dan Lu | Exogenous Variables, Modality Fusion |
| DM729 | Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization | Song Wang, Xiaodong Yang, Rashidul Islam, Huiyuan Chen, Minghua Xu, Jundong Li, and Yiwei Cai | Graph Neural Networks, Distribution Shifts, Out-of-Distribution (OOD) Generalization |
| DM741 | CAKD: A Correlation-Aware Knowledge Distillation Framework Based on Decoupling Kullback-Leibler Divergence | Zao Zhang, Huaming Chen, Pei Ning, and Dong Yuan | Knowledge Distillation, Model Compression, Feature Interpretability. |
| DM749 | Addressing Delayed Feedback in Conversion Rate Prediction: A Domain Adaptation Approach | Leisheng Yu, Yanxiao Cai, Lucas Chen, Minxing Zhang, Wei-Yen Day, Li Li, Rui Chen, Soo-Hyun Choi, and Xia Hu | Delayed Feedback, Computational Advertising |
| DM753 | Hypergraph-Enhanced Contrastively Regularized Transformer for Multi-Behavior E-commerce Product Recommendation | Shuiying Liao and P. Y. Mok | Recommendation, Personalization, E-commerce, Preference Modeling, Data Augmentation. |
| DM780 | An Efficient Graph Autoencoder with Lightweight Desmoothing Decoder and Long-Range Modeling | Jinyong Wen, Chunxia Zhang, Shiming Xiang, and Chunhong Pan | self-supervised graph representation learning, graph autoencoder, lightweight smoothness-aware feature reconstructor, global structural dependency catcher |
| DM795 | Handling Non-IID Data in Federated Learning Using Metaheuristic Optimization Techniques | Amin Birashk, Sadaf MD Halim, and Latifur Khan | Federated Learning, Non-IID Data, Metaheuristic Optimization, Statistical Heterogeneity, Privacy Preservation |
| DM798 | MoRE-LLM: Mixture of Rule Experts Guided by a Large Language Model | Alexander Koebler, Ingo Thon, and Florian Buettner | Large Language Model, Interpretable AI, Explainable AI, Mixture of Experts |
| DM809 | PC3: Enhancing Concurrency in High-Conflict Transactions with Prior Cascading Control | Zhibin Wang, Jiangtao Cui, Xiyue Gao, Hui Zhang, Guiqi Ren, Yixiao Liu, Hui Li, and Kankan Zhao | Transaction Concurrency Control, Transaction Prediction, Concurrency Optimization |
| DM812 | Rank Supervised Contrastive Learning for Time Series Classification | Qianying Ren, Dongsheng Luo, and Dongjin Song | time series classification, representation learning, contrastive learning |
Demo papers
| N | Paper ID | Accept Papers |
|---|---|---|
| 1 | S25201 | Xiachong Lin, Arian Prabowo, Imran Razzak, Hao Xue, Matthew Amos, Sam Behrens, and Flora Salim, BiTSA: Leveraging Time Series Foundation Model for Building Energy Analytics Contact Person: Xiachong Lin dawn.lin@student.unsw.edu.au |
| 2 | S25202 | Ildar Nurgaliev, Andre Kuzminykh, Andrey Savchenko, and Ilya Makarov, Go-Kart Racing Simulator for Reinforcement Learning with Augmented Sim2Real Adaptation Contact Person: Andrey Savchenko avsavchenko@hse.ru |
| 3 | S25203 | Tong Xie, Hanzhi Zhang, Shaozhou Wang, Yuwei Wan, Imran Razzak, Chunyu Kit, Wenjie Zhang, and Bram Hoex, ByteScience: Scientific Information Annotation, Extraction and Inference Platform with Auto Fine-tuned Large Language Model in Token Granularity Contact Person: Tong Xie tong@greendynamics.com.au |
| 4 | S25204 | Maxim Novopoltsev, Aleksandr Tulenkov, Ruslan Murtazin, Roman Akhidov, Iuliia Zemtsova, Emilia Bojarskaja, Daria Bondarenko, Andrey Savchenko, and Ilya Makarov, Video-based learning of sign languages: one pre-train to fit them all Contact Person: Andrey Savchenko avsavchenko@hse.ru |
| 5 | S25205 | Matvey Gerasyov, Dmitrii Kiselev, Maxim Beketov, and Ilya Makarov, VIA AI: Reliable Deep Reinforcement Learning for Traffic Signal Control Contact Person: Matvey Gerasyov msgerasyov@hse.ru |
| 6 | S25206 | Nikita Severin, Aleksei Ziablitsev, Yulia Savelyeva, Valeriy Tashchilin, Ivan Bulychev, Mikhail Yushkov, Artem Kushneruk, Amaliya Zaryvnykh, Dmitrii Kiselev, Andrey Savchenko, and Ilya Makarov, LLM-KT: A Versatile Framework for Knowledge Transfer from Large Language Models to Collaborative Filtering Contact Person: Nikita Severin nseverin@hse.ru |