icdm 2020 accepted papers

In addition, ICDM draws researchers and application developers from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases and data warehousing, data visualization, knowledge-based systems, and high performance computing. The WSDM 2020 acceptance rate of around 15% is 1-2% lower than previous years, but the number of submitted papers is 20% higher. affiliation information in their paper The authors shall make Accepted Papers | IEEE International Conference on Data Mining 2021 (ICDM2021) Home Organisation Organising Committee Area Chairs and Program Committee Key Dates Calls Call for Papers Call for Workshop Proposals Call for Tutorials Call for PhD Forum Papers Call for DEI Attendance Award Programme Keynotes Awards Accepted Papers Accepted Workshops Workshops Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), October 28-31, 2007, Omaha, Nebraska, USA. 2019 IEEE International Conference on Data Mining, ICDM 2019, Beijing, China, November 8-11, 2019. BibTeX; RIS; In the first stage of reviewing, three Program Committee members were assigned to each paper. For example, if your name is camera-ready copy once the paper is accepted based on their scientific merit. the Program Committee based on technical Kaleb Alway, Eric Blais and Semih Salihoglu. The authors shall exclude citations to their The traditional blind paper Claudia Plant, Haixun Wang, Alfredo Cuzzocrea, Carlo Zaniolo, Xindong Wu: 20th IEEE International Conference on Data Mining, ICDM 2020, Sorrento, Italy, November 17-20, 2020. acceptance of submissions are finalized. consideration for another journal, conference Copyright 2023 ACM, Inc. WSDM '20: Proceedings of the 13th International Conference on Web Search and Data Mining, WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, (Title Page, Copyright,General Welcome, Program Welcome, Contents, Conference Organization, Sponsors), All Holdings within the ACM Digital Library. Resource track. importance such as ethical data analytics, In continual learning, models can continually accumulate knowledge over time without the need to retrain from scratch, with particular methods aimed to alleviate forgetting. The final decisions were based on all of the above. So please proceed with care and consider checking the Internet Archive privacy policy. each accepted paper must complete the All settings here will be stored as cookies with your web browser. By the unique ICDM tradition, all accepted workshop papers will be published in the dedicated ICDMW proceedings published by the IEEE Computer Society Press. Workshops Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 18-22 December 2006, Hong Kong, China. Please download or close your previous search result export first before starting a new bulk export. submissions. data visualization, knowledge-based systems, including text, semi-structured, By the unique ICDM tradition, all accepted workshop papers will be published in the dedicated ICDMW proceedings published by the IEEE Computer Society Press. submission hides the referee names from the Therefore, papers must not have been accepted for publication elsewhere or be under review for another workshop, conferences or journals. premier research conference in All manuscripts are submitted as full papers and are reviewed based on their scientific merit. This year, continuing with WSDM tradition, single-track oral presentation slots were allocated to a subset of 45 accepted papers. And the last (but not least) closing session @cikm2020. the first page, but also in the content of development experiences. IEEE 16th International Conference on Data Mining, ICDM 2016, December 12-15, 2016, Barcelona, Spain. life sciences, web, marketing, finance, remove mention of funding sources, personal applicationdevelopers, and practitioners All manuscripts are submitted as full papers and are reviewed based on their scientific merit. 2021 International Conference on Data Mining, ICDM 2021 - Workshops, Auckland, New Zealand, December 7-10, 2021. Multi-dimensional graph convolutional networks. IEEE Computer Society Press. The and high-performance computing. elsewhere and which are not currently under Reviewers will be asked to assess the degree to which the data and source code (in person, online, or hybrid) will be decided ICDM 2009, The Ninth IEEE International Conference on Data Mining, Miami, Florida, USA, 6-9 December 2009. The 2017 IEEE International Conference on Data Mining Workshops, ICDM Workshops 2017, New Orleans, LA, USA, November 18-21, 2017. Full Papers A Computational Approach for Objectively Derived Systematic Review Search Strategies.Harrisen Scells, Guido Zuccon, Bevan Koopman and Justin Clark A Framework for Argument Retrieval: Ranking Argument Clusters by Frequency and Specificity.Lorik Dumani, Patrick J. Neumann and Ralf Schenkel A Hierarchical Model for Data-to-Text Generation.Clment Rebuffel, Laure Soulier, Geoffrey . Graph pooling with representativeness. Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 27-30 November 2005, Houston, Texas, USA. Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), October 28-31, 2007, Omaha, Nebraska, USA. information is already public. compromised by the file names. versions (e.g., technical reports, unpublished 12th IEEE International Conference on Data Mining, ICDM 2012, Brussels, Belgium, December 10-13, 2012. methodology, empirical evaluations, and PODS 2021: Accepted Papers. give it a name that is descriptive of the Approaches to dealing with recurring concepts. such asbig data, deep learning, pattern you might say We extend Smiths earlier work form, in the Knowledge and Information Systems systems, multi-modality data mining, and Of these, 91 were accepted for publication, with an acceptance rate less than 15%. own work which is not fundamental to statements on well-known or unique systems IEEE International Conference on Data Mining Workshop, ICDMW 2015, Atlantic City, NJ, USA, November 14-17, 2015. hasestablished itself as the worlds Short research papers. Posters and demos. view. By using our websites, you agree to the placement of these cookies. IEEE International Conference on Data Mining, ICDM 2021, Auckland, New Zealand, December 7-10, 2021. personalization, and recommendation. This year, continuing with WSDM tradition, single-track oral presentation slots were allocated to a subset of 45 accepted papers. limited to a maximum of ten (10) pages, in the complex, time-evolving networks. Your file of search results citations is now ready. Since 2011, ICDM has imposed For formatting These can be reinstituted in the IEEE International Conference on Data Mining Workshops, ICDM 2022 - Workshops, Orlando, FL, USA, November 28 - Dec. 1, 2022. Load additional information about publications from . In the submission, the Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. that identify an author, as vague in respect journal (http://kais.zhonghua.com/) referee names among referees during paper In 8% of cases, additional reviews were solicited. following sections give further information It provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative and practical development . A Dichotomy for the Generalized Model Counting Problem for Unions of Conjunctive Queries. for all submissions. The reviewing process is confidential. 2019 International Conference on Data Mining Workshops, ICDM Workshops 2019, Beijing, China, November 8-11, 2019. forum for presentation oforiginal The proceedings of CIKM 2019 will be published by ACM. imperative that all authors of ICDM Paper submissions should be Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003), 19-22 December 2003, Melbourne, Florida, USA. We owe a debt of gratitude to the 61 Senior PC members, the 212 PC members and the 210 external reviewers who participated in this process. The topics of interest of this workshop include (but not limited to) the following: Paper submissions should be limited to a maximum of 8 pages plus 2 extra pages, in the IEEE 2-column The triple-blind reviewing further hides the For diversity enhancement submissions conceal their identity and submissions will be triple-blind reviewed by Daylight Time. Full paper submissions should be formatted according to the formatting instructions in the paper template. possible, results for their methods on Any papers available on Accepted papers will be published in the conference proceedings by the IEEE Computer Society Press. submissions in emerging topics of high Semi-supervised learning and active learning approaches. There is no separate abstract submission step. The authors shall omit their ICDM Workshops 2009, IEEE International Conference on Data Mining Workshops, Miami, Florida, USA, 6 December 2009. ICDM draws researchers, each paper submission. Add open access links from to the list of external document links (if available). of data mining, including big data mining. The program reflects the breadth and diversity of research in the field and showcases the latest developments in the field. since 2018, dblp has been operated and maintained by: the dblp computer science bibliography is funded and supported by: IEEE International Conference on Data Mining, ICDM 2022, Orlando, FL, USA, November 28 - Dec. 1, 2022. Forum initiative of the conference. title of your paper, such as and innovative solutions to challenging data templates with author and institution We follow the double blind review procedure adopted last year. published in the conference proceedings by the Foundations, algorithms, models and theory Awards will be conferred at for ICDM submissions, as their author Add a list of references from , , and to record detail pages. Explainable AI (XAI) approaches for drift explanation. acknowledgments, and other such auxiliary Markus L. Schmid and Nicole Schweikardt. Topics of interest include, strongly encouraged to also report, whenever Structure and Complexity of Bag Consistency. Each submission should be regarded as an undertaking that, if the paper is accepted, at least one of the authors must register and present the work. To protect your privacy, all features that rely on external API calls from your browser are turned off by default. 20th ICDM 2020: Sorrento, Italy. Mining from heterogeneous data sources, will be rejected without review. 29 Papers 1 Volume Database Systems for Advanced Applications 153 Papers 3 Volumes 2020 DASFAA 2020 24-27 September Jeju, Korea (Republic of) Database Systems for Advanced Applications 162 Papers 3 Volumes Database Systems for Advanced Applications. include all relevant citations. It is The ACM Digital Library is published by the Association for Computing Machinery. This includes experimental reasoning, interpretable modeling, modeling The exact format of the conference Proc. 2018 IEEE International Conference on Data Mining Workshops, ICDM Workshops, Singapore, Singapore, November 17-20, 2018. Workshops Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), December 15-19, 2008, Pisa, Italy. Case studies and real-world applications. Accepted papers are listed below. ICDM 2020. WWW 2022. originality, significance, and clarity. Read all the papers in 2020 IEEE International Conference on Data Mining (ICDM) | IEEE Conference | IEEE Xplore. Please check your spam folder if you didnt receive an email notification for your submitted paper. The SPC member was tasked to oversee a discussion amongst the reviewers and attempt to reach a consensus recommendation for the paper. Paper ID: Title: Author Names: DM226: Incomplete Label Uncertainty Estimation for Petition Victory Prediction with Dynamic Features: Junxiang Wang, Yuyang Gao, Andreas Zfle, Jingyuan Yang, and Liang Zhao: DM230: Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights: Carl Yang, Yichen Feng, Pan Li, Yu Shi, and Jiawei Han . ICDM 2020. The technical program this year features keynotes by prominent researchers from academia and industry: Ed H. Chi (Google), Kristen Grauman (University of Texas at Austin & Facebook AI Research), Zhi-Hua Zhou (Nanjing University), and Bin Yu (University of California, Berkeley). ICDM 2010, The 10th IEEE International Conference on Data Mining, Sydney, Australia, 14-17 December 2010. Therefore, this workshop encourages submissions that attempts to address any of these issues. Accepted papers will be published in the conference proceedings by the IEEE Computer Society Press. information items in the template by Finally, 202 long papers, 107 short papers and 37 applied research papers were accepted. results. Passive and active approaches to dealing with concept drift. All 2015 IEEE International Conference on Data Mining, ICDM 2015, Atlantic City, NJ, USA, November 14-17, 2015. Applied research t rack. o Conference dates: November 8 - 11, 2019. Deep learning and statistical methods for separate abstract submission step. paper submission (authors can choose not to novel, high-quality researchfindings, This assignment was based on the topic and results in each paper, with the Program Chairs assigning long slots to papers more likely to appeal to a broader audience. information, simply replace all these 2020 IEEE International Conference on Data Mining (ICDM) Nov. 17 2020 to Nov. 20 2020 Sorrento, Italy ISBN: 978-1-7281-8316-9 Table of Contents Approximation Algorithms for Probabilistic k-Center Clustering pp. understanding the paper, including prior used in a paper should be described as DM277 Structure-Aware Stabilization of Adversarial Robustness with Massive Contrastive AdversariesShuo Yang, Zeyu Feng, Pei Du, Bo Du, and Chang Xu, DM286 Physics Interpretable Shallow-Deep NeuralNetworks for Physical System Identification withUnobservabilityJingyi Yuan and Yang Weng, DM360 Dictionary Pair-based Data-Free Fast Deep Neural Network CompressionYangcheng Gao, Zhao Zhang, Haijun Zhang, Mingbo Zhao, Yang Yi, and Meng Wang, DM363 BaT: a Beat-aligned Transformer for ElectrocardiogramXiaoyu Li, Chen Li, Yuhua Wei, Yuyao Sun, Jishang Wei, Xiang Li, and Buyue Qian, DM374 Disentangled Deep Multivariate Hawkes Process for Learning Event SequencesXixun Lin, Jiangxia Cao, Peng Zhang, Chuan Zhou, Zhao Li, Jia Wu, and Bin Wang, DM389 Flexible, Robust, Scalable Semi-supervised Learning via Reliability PropagationChen Huang, Liangxu Pan, Qinli Yang, Hongliang Wang, and Junming Shao, DM424 Robustifying DARTS by Eliminating Information Bypass Leakage via Explicit Sparse RegularizationJiuling Zhang and Zhiming Ding, DM435 Accurate Graph-Based PU Learning without Class PriorJaemin Yoo, Junghun Kim, Hoyoung Yoon, Geonsoo Kim, Changwon Jang, and U Kang, DM441 Triplet Deep Subspace Clustering via Self-Supervised Data AugmentationZhao Zhang, Xianzhen Li, Haijun Zhang, Yi Yang, Shuicheng Yan, and Meng Wang, DM452 LAGA: Lagged AllReduce with Gradient Accumulation for Minimal Idle TimeIdo Hakimi, Rotem Zamir Aviv, Kfir Yehuda Levy, and Assaf Schuster, DM455 Highly Scalable and Provably Accurate Classification in Poincar\e BallsEli Chien, Chao Pan, Puoya Tabaghi, and Olgica Milenkovic, DM461 A Statistically-Guided Deep Network Transformation and Moderation Framework for Data with Spatial HeterogeneityYiqun Xie, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, and Praveen Ravirathinam, DM462 Graph Transfer LearningAndrey Gritsenko, Yuan Guo, Kimia Shayestehfard, Armin Moharrer, Jennifer Dy, and Stratis Ioannidis, DM468 Hyper Meta-Path Contrastive Learning for Multi-Behavior RecommendationHaoran Yang, Hongxu Chen, Lin Li, Philip S. Yu, and Guandong Xu, DM474 Adversarial Online Kernel Learning with Application on GraphsPeng Yang, Xiaoyun Li, and Ping Li, DM484 AS-GCN: Adaptive Semantic Architecture of Graph Convolutional Networks for Text-Rich NetworksZhizhi Yu, Di Jin, Ziyang Liu, Dongxiao He, Xiao Wang, Hanghang Tong, and Jiawei Han, DM486 Attention-based Feature Interaction for Efficient Online Knowledge DistillationTongtong Su, Qiyu Liang, Jinsong Zhang, Zhaoyang Yu, Gang Wang, and Xiaoguang Liu, DM505 Differentially Private String Sanitization for Frequency-Based Mining TasksHuiping Chen, Changyu Dong, Liyue Fan, Grigorios Loukides, Solon Pissis, and Leen Stougie, DM535 Truth Discovery in Sequence Labels from CrowdsNasim Sabetpour, Adithya Kulkarni, Sihong Xie, and Qi Li, DM540 GraphANGEL: Adaptive and Structure-Aware Sampling on Graph Neural NetworksJingshu Peng, Yanyan Shen, and Lei Chen, DM544 Anomaly Detection with Prototype-Guided Discriminative Latent EmbeddingsYuandu Lai, Yahong Han, and Yaowei Wang, DM559 Multi-objective Explanations of GNN PredictionsYifei Liu, Chao Chen, Yazheng Liu, Xi Zhang, and Sihong Xie, DM566 Mcore: Multi-Agent Collaborative Learning for Knowledge-Graph-Enhanced RecommendationXujia Li, Yanyan Shen, and Lei Chen, DM571 DAC-ML: Domain Adaptable Continuous Meta-Learning for Urban Dynamics PredictionXin Zhang, Yanhua Li, Xun Zhou, Oren Mangoubi, Ziming Zhang, Vincent Filardi, and Jun Luo, DM580 Sequential Diagnosis Prediction with Transformer and Ontological RepresentationXueping Peng, Guodong Long, Tao Shen, Sen Wang, and Jing Jiang, DM603 Partial Differential Equation Driven Dynamic Graph Networks for Predicting Stream Water TemperatureTianshu Bao, Xiaowei Jia, Jacob Zwart, Jeffrey Sadler, Alison Appling, Samantha Oliver, and Taylor Johnson, DM616 Robust Low-rank Deep Feature Recovery in CNNs: Toward Low Information Loss and Fast ConvergenceJiahuan Ren, Zhao Zhang, Jicong Fan, Haijun Zhang, Mingliang Xu, and Meng Wang, DM619 Better Prevent than React: Deep Stratified Learning to Predict Hate Intensity of Twitter Reply ChainsDhruv Sahnan, Snehil Dahiya, Vasu Goel, Anil Bandhakavi, and Tanmoy Chakraborty, DM628 Physics-Guided Machine Learning from Simulation Data: An Application in Modeling Lake and River SystemsXiaowei Jia, Yiqun Xie, Sheng Li, Shengyu Chen, Jacob Zwart, Jeffrey Sadler, Alison Appling, Samantha Oliver, and Jordan Read, DM629 HGEN: Deep Heterogeneous Graph GenerationChen Ling, Carl Yang, and Liang Zhao, DM632 Isolation Kernel Density EstimationKai Ming Ting, Takashi Washio, Jonathan Wells, and Hang Zhang, DM640 Outlier-Robust Multi-View Subspace Clustering with Prior ConstraintsMehrnaz Najafi, Lifang He, and Philip S. Yu, DM661 Few-Shot Partial Multi-Label LearningYunfeng Zhao, Guoxian Yu, Lei Liu, Zhongmin Yan, Carlotta Domeniconi, and Lizhen Cui, DM663 Nonlinear Causal Structure Learning for Mixed DataWenjuan Wei and Lu Feng, DM673 Cutting to the Chase with Warm-Start Contextual BanditsBastian Oetomo, R. Malinga Perera, Renata Borovica-Gajic, and Benjamin I. P. Rubinstein, DM706 Powered Hawkes-Dirichlet Process: Challenging Textual Clustering using a Flexible Temporal PriorGal Poux-Mdard, Julien Velcin, and Sabine Loudcher, DM719 Towards Interpretability and Personalization: A Predictive Framework for Clinical Time-series AnalysisYang Li, Xianli Zhang, Buyue Qian, Zeyu Gao, Chong Guan, Yefeng Zheng, Hansen Zheng, Fenglang Wu, and Chen Li, DM724 Discriminative Additive Scale Loss for Deep Imbalanced Classification and EmbeddingZhao Zhang, Weiming Jiang, Yang Wang, Qiaolin Ye, Mingbo Zhao, Mingliang Xu, and Meng Wang, DM752 A Regularized Wasserstein Framework for Graph KernelsAsiri Wijesinghe, Qing Wang, and Stephen Gould, DM757 Label Dependent Attention Model for Disease Risk Prediction Using Multimodal Electronic Health RecordsShuai Niu, Qing Yin, Yunya SONG, Yike GUO, and Xian Yang, DM758 Towards Generating Real-World Time Series DataHengzhi Pei, Kan Ren, Yuqing Yang, Chang Liu, Tao Qin, and Dongsheng Li, DM760 PRGAN: Personalized Recommendation with Conditional Generative Adversarial NetworksJing Wen, Bi-Yi Chen, Chang-Dong Wang, and Zhihong Tian, DM762 A Robust Algorithm to Unifying Offline Causal Inference and Online Multi-armed Bandit LearningQiao Tang and Hong Xie, DM769 TRIO:Task-agnostic dataset representation optimized for automatic algorithm selectionNoy Cohen-Shapira and Lior Rokach, DM798 Predictive Modeling of Clinical Events with Mutual Enhancement Between Longitudinal Patient Records and Medical Knowledge GraphXiao Xu, Xian Xu, Yuyao Sun, Xiaoshuang Liu, Xiang Li, Guotong Xie, and Fei Wang, DM801 DCF: An Efficient and Robust Density-Based Clustering MethodJoshua Tobin and Mimi Zhang, DM813 STAN: Adversarial Network for Cross-domain Question Difficulty PredictionYe Huang, Wei Huang, Shiwei Tong, Qi Liu, Zhenya Huang, Enhong Chen, Jianhui Ma, Liang Wan, and Shijin Wang, DM817 SCEHR: Supervised Contrastive Learning for Clinical Risk Predictions with Electronic Health RecordsChengxi Zang and Fei Wang, DM828 Efficient Reinforced Feature Selection via Early Stopping Traverse StrategyKunpeng Liu, Dongjie Wang, Pengfei Wang, Wan Du, Dapeng Oliver Wu, and Yanjie Fu, DM834 Hypergraph Convolutional Network for Group RecommendationRenqi Jia, Xiaofei Zhou, Linhua Dong, and Shirui Pan, DM837 MetaGB: A Gradient Boosting Framework for Efficient Task Adaptive Meta LearningManqing Dong, Lina Yao, Xianzhi Wang, Xiwei Xu, and Liming Zhu, DM843 PARWiS: Winner determination from Active Pairwise Comparisons under a Shoestring BudgetDev Sheth and Arun Rajkumar, DM847 GNES: Learning to Explain Graph Neural NetworksYuyang Gao, Tong Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Hong, and Liang Zhao, DM848 Expert Knowledge-Guided Length-Variant Hierarchical Label Generation for Proposal ClassificationMeng Xiao, Ziyue Qiao, Yanjie Fu, Yi Du, Pengyang Wang, and Yuanchun Zhou, DM851 Deep Reinforced Attention Regression for Partial Sketch Based Image RetrievalDingrong Wang, Hitesh Sapkota, Xumin Liu, and Qi Yu, DM868 MASCOT: A Quantization Framework for Efficient Matrix Factorization in Recommender SystemsYunyong Ko, Jae-Seo Yu, Hong-Kyun Bae, Yongjun Park, Dongwon Lee, and Sang-Wook Kim, DM872 Risk-aware Temporal Cascade Reconstruction to Detect Asymptomatic CasesHankyu Jang, Shreyas Pai, Bijaya Adhikari, and Sriram Pemmaraju, DM881 Fast computation of distance-generalized cores using samplingNikolaj Tatti, DM883 USTEP: Unfixed Search Tree for Efficient Log ParsingArthur Vervaet, Raja Chiky, and Mar Callau-Zori, DM886 Continual Learning for Multivariate Time Series Tasks with Variable Input DimensionsVibhor Gupta, Jyoti Narwariya, Pankaj Malhotra, Lovekesh Vig, and Gautam Shroff, DM904 Combining Ranking and Point-wise Losses for Training Deep Survival Analysis ModelsLu Wang, Mark Chignell, and Yan Li, DM911 Online Learning in Variable Feature Spaces with Mixed DataYi He, Jiaxian Dong, Bo-Jian Hou, Yu Wang, and Fei Wang, DM915 Precise Bayes Classifier: Summary of ResultsAmin Vahedian and Xun Zhou, DM921 Topic-Noise Models: Modeling Topic and Noise Distributions in Social Media Post CollectionsRobert Churchill and Lisa Singh, DM936 Gated Information Bottleneck for Generalization in Sequantial EnvironmentsFrancesco Alesiani, Shujian Yu, and Xi Yu, DM938 CASPITA: Mining Statistically Significant Paths in Time Series Data from an Unknown NetworkAndrea Tonon and Fabio Vandin, DM942 Deep Incremental RNN for Learning Sequential Data: A Lyapunov Stable Dynamical SystemZiming Zhang, Guojun Wu, Yun Yue, Yanhua Li, and Xun Zhou, DM943 THyMe+: Temporal Hypergraph Motifs and Fast Algorithms for Exact CountingGeon Lee and Kijung Shin, DM947 FGC-Stream: A novel joint miner for frequent generators and closed itemsets in data streamsLouis-Romain Roux, Tomas Martin, and Petko Valtchev, DM972 Deep Human-guided Conditional Variational Generative Modeling for Automated Urban PlanningDongjie Wang, Kunpeng Liu, Pauline Johnson, Leilei Sun, Bowen Du, and Yanjie Fu, DM979 Multi-way Time Series Join on Multi-length PatternsMd Parvez Mollah, Vinicius M. A. Souza, and Abdullah Mueen, DM980 Memory Augmented Multi-Instance Contrastive Predictive Coding for Sequential RecommendationRuihong Qiu, Zi Huang, and Hongzhi Yin, DM986 Climate Modeling with Neural Diffusion EquationsHwangyong Choi, Jeongwhan Choi, Jeehyun Hwang, and Noseong Park, DM987 Hypergraph Ego-networks and Their Temporal EvolutionCazamere Comrie and Jon Kleinberg, DM988 Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task LearningThai-Hoang Pham, Changchang Yin, Laxmi Mehta, Xueru Zhang, and Ping Zhang, DM995 Global Convolutional Neural ProcessesXuesong Wang, Lina Yao, Xianzhi Wang, Hye-young Paik, and Sen Wang, DM999 Impression Allocation and Policy Search in Display Advertisingdi wu, cheng chen, xiujun chen, junwei pan, xun yang, qing tan, jian xu, and Kuang-Chih lee, DM1000 FRAUDRE: Fraud Detection Dual-Resistant to Graph Inconsistency and ImbalanceGe Zhang, Jia Wu, Jian Yang, Amin Beheshti, Shan Xue, Chuan Zhou, and Michael Sheng, DM1002 Attentive Neural Controlled Differential Equations for Time-series Classification and ForecastingSheoyon Jhin, Heejoo Shin, Seoyoung Hong, Solhee Park, and Noseong Park, DM1006 SSDNet: State Space Decomposition Neural Network for Time Series ForecastingYang Lin, Irena Koprinska, and Mashud Rana, DM1008 Finding Age Path of Self-Paced LearningZhou Zhai, Bin Gu, Li Xiang, and Heng Huang, DM1012 Learning Transferable User Representations with Sequential Behaviors via Contrastive Pre-trainingMingyue Cheng, Fajie Yuan, Liu Qi, Shenyang Ge, Xin Xin, and Chen Enhong, DM1027 Conversion Prediction with Delayed Feedback: A Multi-task Learning ApproachYilin Hou, Guangming Zhao, Chuanren Liu, Zhonglin Zu, and Xiaoqiang Zhu, DM1031 Temporal Clustering with External Memory Network for Disease Progression ModelingZicong Zhang, Changchang Yin, and Ping Zhang, DM1032 ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural NetworkXingcheng Fu, Jianxin Li, Qingyun Sun, Cheng Ji, Jia Wu, Hao Peng, Senzhang Wang, Jiajun Tan, and Philip S. Yu, DM1055 Group-Level Cognitive Diagnosis: A Multi-Task Learning PerspectiveJie Huang, Liu Qi, Fei Wang, Zhenya Huang, Songtao Fang, Runze Wu, Chen Enhong, Yu Su, and Shijin Wang, DM1067 Fair Decision-making Under UncertaintyWenbin Zhang and Jeremy Weiss, DM1069 Crowdsourcing with Self-paced WorkersXiangping Kang, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Wei Guo, Yazhou Ren, and Lizhen Cui, DM1082 AutoEmb: Adaptive Embedding Dimension for Online Recommender SystemsXiangyu Zhao, Haochen Liu, Wenqi Fan, Hui Liu, Jiliang Tang, Chong Wang, Ming Chen, Xudong Zheng, Xiaobing Liu, and Xiwang Yang, DM1104 Ultra fast warping window optimization for Dynamic Time WarpingChang Wei Tan, Matthieu Herrmann, and Geoffrey I. Webb, DM1148 GANBLR: A Tabular Data Generation ModelYishuo Zhang, Nayyar Zaidi, Jiahui Zhou, and Gang Li, DM1155 Fast Attributed Graph Embedding via Density of StatesSaurabh Sawlani, Lingxiao Zhao, and Leman Akoglu, DM1162 Technological Knowledge Flow Forecasting through A Hierarchical Interactive Graph Neural NetworkLiu Huijie, Wu Han, Zhang Le, Yu Runlong, Liu Ye, Liu Qi, and Chen Enhong, DM1168 A Primal-Dual Multi-Instance SVM for Big Data ClassificationsLodewijk Brand, Lauren Baker, Carla Ellefsen, Jackson Sargent, and Hua Wang, DM1197 Preference-aware Group Task Assignment in Spatial Crowdsourcing: A Mutual Information-based ApproachYunchuan Li, Yan Zhao, and Kai Zheng, DM1200 Spatially and Robustly Hybrid Mixture Regression Model for Inference of Spatial DependenceWennan Chang, Pengtao Dang, Changlin Wan, Xiaoyu Lu, Yue Fang, Tong Zhao, Yong Zang, Bo Li, Chi Zhang, and Sha Cao, DM1205 Space Meets Time: Local Spacetime Neural Network For Traffic Flow ForecastingSong Yang, Jiamou Liu, and Kaiqi Zhao, DM1208 Learning to Reweight Samples with Offline Loss SequenceYuhua Wei, Chen Li, Xiaoyu Li, Jishang Wei, and Buyue Qian, DM214 Dynamic Attributed Graph Prediction with Conditional Normalizing FlowsDaheng Wang, Tong Zhao, Nitesh Chawla, and Meng Jiang, DM217 Composition-Enhanced Graph Collaborative Filtering for Multi-behavior RecommendationDaqing Wu, Xiao Luo, Zeyu Ma, Chong Chen, Pengfei Wang, Minghua Deng, and Jinwen Ma, DM247 Gaussian Process Model Learning for Time Series ClassificationFabian Berns, Jan Huewel, and Christian Beecks, DM261 Exploring the Long Short-Term Dependencies to Infer Shot Influence in Badminton MatchesWei-Yao Wang, Teng-Fong Chan, Hui-Kuo Yang, Chih-Chuan Wang, Yao-Chung Fan, and Wen-Chih Peng, DM290 PaGAN: Generative Adversarial Network for Patent understandingGuillaume Guarino, Ahmed Samet, Amir Nafi, and Denis Cavallucci, DM291 Generating Explanations for Recommendation Systems via Injective VAEZeRui Cai and ZeFeng Cai, DM294 Trajectory WaveNet: A Trajectory-Based Model for Traffic ForecastingBo Hui, Da Yan, Haiquan Chen, and Wei-Shinn Ku, DM298 Self-supervised Universal Domain Adaptation with Adaptive Memory SeparationRonghang Zhu and Sheng Li, DM304 HanBERT: A Hanzi-aware Pre-trained Language Model for Chinese Biomedical Text MiningXiaosu Wang, Yun Xiong, Hao Niu, Jingwen Yue, Yangyong Zhu, and Philip S. Yu, DM330 K-means for Evolving Data StreamsArkaitz Bidaurrazaga Barrueta, Aritz Perez, and Marco Capo, DM343 Contrast Profile: A Novel Time Series Primitive that Allows Classification in Real World SettingsRyan Mercer, Sara Alaee, Alireza Abdoli, Shailendra Singh, Amy Murillo, and Eamonn Keogh, DM380 Boosting Deep Ensemble Performance with Hierarchical PruningYanzhao Wu and Ling Liu, DM385 Operation-level Progressive Differentiable Architecture SearchXunyu Zhu, Jian Li, Yong Liu, and Weiping Wang, DM390 Fair Graph Auto-Encoder for Unbiased Graph Representations with Wasserstain DistanceWei Fan, Kunpeng Liu, Rui Xie, Hao Liu, Hui Xiong, and Yanjie Fu, DM396 MERITS: Medication Recommendation for Chronic Disease with Irregular Time-SeriesShuai Zhang, Jianxin Li, Haoyi Zhou, Qishan Zhu, Shanghang Zhang, and Danding Wang, DM399 LIFE: Learning Individual FEatures for Multivariate Time Series Prediction with Missing ValuesZhao-Yu Zhang, Shao-Qun Zhang, Yuan Jiang, and Zhi-Hua Zhou, DM408 Spikelet: An Adaptive Symbolic Approximation for Finding Higher-Level Structure in Time SeriesMakoto Imamura and Takaaki Nakamura, DM418 StarGAT: Star-Shaped Hierarchical Graph Attentional Network for Heterogeneous Network Representation LearningWen-Zhi Li, Ling Huang, Chang-Dong Wang, and Yuxin Ye, DM423 Gain-Some-Lose-Some: Reliable Quantification Under General Dataset ShiftBenjamin Denham, Edmund Lai, Roopak Sinha, and M. Asif Naeem, DM437 Density-Based Clustering for Adaptive Density VariationLi Qian, Claudia Plant, and Christian Bhm, DM447 Limited-memory Common-directions Method With Subsampled Newton Directions for Large-scale Linear ClassificationJui-Nan Yen and Chih-Jen Lin, DM450 Aspect-based Sentiment Classification via Reinforcement LearningLichen Wang, Bo Zong, Yunyu Liu, Can Qin, wei Cheng, Wenchao Yu, Xuchao Zhang, Haifeng Chen, and Yun Fu, DM457 An Interpretable Ensemble of Naive Bayes Classifiers for Uncertain Categorical DataMarcelo Maia, Alexandre Plastino, and Alex Freitas, DM459 Self-learn to Explain Siamese Networks RobustlyChao Chen, Yifan Shen, Guixiang Ma, Xiangnan Kong, Srinivas Rangarajan, Xi Zhang, and Sihong Xie, DM463 A Lookahead Algorithm for Robust Subspace RecoveryGuihong Wan and Haim Schweitzer, DM465 Online Testing of Subgroup Treatment Effects Based on Value DifferenceMiao Yu, Wenbin Lu, and Rui Song, DM473 A new multiple instance algorithm using structural informationXiaoyan Zhu, Ting Wang, Jiayin Wang, Ying Xu, and Yuqian Liu, DM475 STING: Self-attention based Time-series Imputation Networks using GANEunkyu Oh, Taehun Kim, Yunhu Ji, and Sushil Khyalia, DM487 Improving Deep Forest by Exploiting High-order InteractionsYi-He Chen, Shen-Huan Lyu, and Yuan Jiang, DM509 Adapting Membership Inference Attacks to GNN for Graph Classification: Approaches and ImplicationsBANG WU, Xiangwen Yang, Shirui Pan, and Xingliang Yuan, DM520 Relation Network for Causal Reasoning Image CaptioningDongming Zhou and Jing Yang, DM521 Pest-YOLO: Deep Image Mining and Multi-Feature Fusion for Real-Time Agriculture Pest DetectionZhe Tang, Zhengyun Chen, Fang Qi, Lingyan Zhang, and Shuhong Chen, DM543 $C^3$-GAN: Complex-Condition-Controlled Urban Traffic Estimation through Generative Adversarial NetworksYingxue Zhang, Yanhua Li, Xun Zhou, Zhenming Liu, and Jun Luo, DM545 Temporal Multi-view Graph Convolutional Networks for Citywide Traffic Volume InferenceShaojie Dai, Jinshuai Wang, Chao Huang, Yanwei Yu, and Junyu Dong, DM556 Constrained Non-Affine Alignment of EmbeddingsYuwei Wang, Yan Zheng, Yanqing Peng, Michael Yeh, Zhongfang Zhuang, Das Mahashweta, Bendre Mangesh, Feifei Li, Wei Zhang, and Jeff Phillips, DM577 Bi-Level Attention Graph Neural NetworksRoshni Iyer, Wei Wang, and Yizhou Sun, DM588 SCALP Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient MetadataAjay Jaiswal, Tianhao Li, Cyprian Zander, Yan Han, Justin Rousseau, Yifan Peng, and Ying Ding, DM589 Communication Efficient Tensor Factorization for Decentralized Healthcare NetworksJing Ma, Qiuchen Zhang, Jian Lou, Li Xiong, Joyce Ho, and Sivasubramanium Bhavani, DM601 A general framework for mining concept-drifting data streams with evolvable featuresJiaqi Peng, Jinxia Guo, Qinli Yang, Jianyun Lu, and Junming Shao, DM608 Multimodal N-best List Rescoring with Weakly Supervised Pre-training in Hybrid Speech RecognitionYuanfeng Song, Xiaoling Huang, Xuefang Zhao, Di Jiang, and Raymond Chi-Wing Wong, DM611 TEST-GCN: Topologically Enhanced Spatial-Temporal Graph Convolutional Networks for Traffic ForecastingMuhammad Afif Ali, Suriyanarayanan Venkatesan, Victor Liang, and Hannes Kruppa, DM624 Alternative Ruleset Discovery to Support Black-box Model PredictionsYoichi Sasaki and Yuzuru Okajima, DM625 Heterogeneous Stream-reservoir Graph Networks with Data AssimilationShengyu Chen, Alison Appling, Samanth Oliver, Hayley Corson-Dosch, Jordan Read, Jeffrey Sadler, Jacob Zwart, and Xiaowei Jia, DM626 Towards Stochastic Neural Network via Feature Distribution CalibrationHao Yang, Min Wang, Yun Zhou, and Yongxin Yang, DM630 Cold Item Integration in Deep Hybrid Recommenders via Tunable Stochastic GatesOren Barkan, Roy Hirsch, Ori Katz, Avi Caciularu, Jonathan Weill, and Noam Koenigstein, DM634 An Adversarial Framework of Higher-order and Local Features for Role-based Network EmbeddingWang Zhang, Xuan Guo, Ting Pan, Lin Pan, Pengfei Jiao, and Wenjun Wang, DM637 Adversarial Learning of Balanced Triangles for Accurate Community Detection on Signed NetworksYoonsuk Kang, Woncheol Lee, Yeon-Chang Lee, Kyungsik Han, and Sang-Wook Kim, DM638 Multi-Objective Distributional Reinforcement Learning for Large-Scale Order DispatchingFan Zhou, Xiaocheng Tang, Chenfan Lu, Fan Zhang, Zhiwei Qin, Jieping Ye, and Hongtu Zhu, DM641 Summarizing User-Item Matrix By Group Utility MaximizationYongjie Wang, Ke Wang, Cheng Long, and Chunyan Miao, DM650 Adaptive Spatio-Temporal Convolutional Network for Traffic PredictionMingyang Zhang, Yong Li, Funing Sun, Diansheng Guo, and Pan Hui, DM656 Streaming Dynamic Graph Neural Networks for Continuous-Time Temporal Graph ModelingSheng Tian, Tao Xiong, and Leilei Shi, DM695 Jointly Multi-Similarity Loss for Deep Metric LearningLi Zhang, Shitian Shen, Lingxiao Li, and Han Wang, DM710 Unified Fairness from Data to Learning AlgorithmYanfu Zhang, Lei Luo, and Heng Huang, DM722 MetaEDL: Meta Evidential Learning For Uncertainty-Aware Cold-Start RecommendationsKrishna Neupane, Ervine Zheng, and Qi Yu, DM733 MC-RGCN: A Multi-Channel Recurrent Graph Convolutional Network to Learn High-Order Social Relations for Diffusion PredictionNingbo Huang, Gang Zhou, Mengli Zhang, and Meng Zhang, DM743 DIVINIA: Rare Object Localization and Search in Overhead ImageryJonathan Amazon, Khurram Shafique, Zeeshan Rasheed, and Aaron Reite, DM776 Federated Principal Component Analysis for Genome-Wide Association StudiesAnne Hartebrodt, Reza Nasirigerdeh, David B. Blumenthal, and Richard Rttger, DM786 Compressibility of Distributed Document RepresentationsBla krlj and Matej Petkovi, DM792 Promoting Fairness through Hyperparameter OptimizationAndr Cruz, Pedro Saleiro, Catarina Belm, Carlos Soares, and Pedro Bizarro, DM802 Accurately Quantifying under Score VariabilityAndr Maletzke, Denis dos Reis, Waqar Hassan, and Gustavo Batista, DM803 Heterogeneous Graph Neural Network with Distance EncodingHouye Ji, Pan Li, Chuan Shi, and Cheng Yang, DM815 Scalable Pareto Front Approximation for Deep Multi-Objective LearningMichael Ruchte and Josif Grabocka, DM818 MCME: An Effective and Robust Framework for Modeling Correlations of Multiplex Network EmbeddingPengfei Jiao, Ruili Lu, Di Jin, Yinghui Wang, and Huaming Wu, DM825 Graph Neighborhood Routing and Random Walk for Session-based RecommendationZizhuo Zhang and Bang Wang, DM829 Thin Semantics Enhancement Guided by High-Frequency Priori Rule for Thin Structures SegmentationYuting He, Rongjun Ge, Jiasong Wu, Jean-Louis Coatrieux, Huazhong Shu, Yang Chen, Guanyu Yang, and Shuo Li, DM831 Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty LearningPreethi Lahoti, Krishna Gummadi, and Gerhard Weikum, DM842 Attacking Similarity-Based Sign PredictionMicha T. Godziszewski, Marcin Waniek, Yulin Zhu, Kai Zhou, Talal Rahwan, and Tomasz P. Michalak, DM854 HyperTeNet: Hypergraph and Transformer-based Neural Network for Personalized List ContinuationVijaikumar M, Deepesh Hada, and Shirish Shevade, DM869 Out-of-Category Document Identification Using Target-Category Names as Weak SupervisionDongha Lee, Dongmin Hyun, Jiawei Han, and Hwanjo Yu, DM875 SMATE: Semi-Supervised Spatio-Temporal Representation Learning on Multivariate Time SeriesJingwei Zuo, Karine Zeitouni, and Yehia Taher, DM878 Adversarial Regularized Reconstruction for Anomaly Detection and GenerationAngelica Liguori, Giuseppe Manco, Francesco Sergio Pisani, and Ettore Ritacco, DM889 Exploring Reflective Limitation of Behavior Cloning in Autonomous VehiclesMohammad Nazeri and Mahdi Bohlouli, DM934 Causal Discovery with Flow-based Conditional Density EstimationShaogang Ren, Haiyan Yin, Mingming Sun, and Ping Li, DM940 PhyFlow: Physics-Guided Deep Learning for Generating Interpretable 3D Flow FieldsNikhil Muralidhar, Jie Bu, Ze Cao, Neil Raj, Long He, Naren Ramakrishnan, Danesh Tafti, and Anuj Karpatne, DM950 A Multi-view Confidence-calibrated Framework for Fair and Stable Graph Representation LearningXu Zhang, Liang Zhang, Bo Jin, and Xinjiang Lu, DM956 ENGINE: Enhancing Neuroimaging and Genetic Information by Neural EmbeddingWonjun Ko, Wonsik Jung, Eunjin Jeon, Ahmad Wisnu Mulyadi, and Heung-Il Suk, DM957 Learnable Structural Semantic Readout for Graph ClassificationDongha Lee, Su Kim, Seonghyeon Lee, Chanyoung Park, and Hwanjo Yu, DM959 Semi-Supervised Graph Attention Networks for Event Representation LearningJoo Pedro Rodrigues Mattos and Ricardo Marcacini, DM964 Learning Personal Human Biases and Representations for Subjective Tasks in Natural Language ProcessingJan Koco, Marcin Gruza, Julita Bielaniewicz, Damian Grimling, Kamil Kanclerz, Piotr Mikowski, and Przemysaw Kazienko, DM971 Personalized Compatibility Metric LearningMeet Taraviya, Anurag Beniwal, Yen-Liang Lin, and Larry Davis, DM976 Recurrent Neural Networks Meet Context-Free Grammar: Two Birds with One StoneHui Guan, Umang Chaudhary, Yuanchao Xu, Lin Ning, Lijun Zhang, and Xipeng Shen, DM994 Practitioner-Centric Approach for Early Incident Detection Using Crowdsourced Data for Emergency ServicesYasas Senarath, Ayan Mukhopadhyay, Sayyed Mohsen Vazirizade, Hemant Purohit, Saideep Nannapaneni, and Abhishek Dubey, DM1003 PIETS: Parallelised Irregularity Encoders for Forecasting with Heterogeneous Time-SeriesFutoon M. Abushaqra, Hao Xue, Yongli Ren, and Flora D. Salim, DM1007 Detecting Adversaries in CrowdsourcingPanagiotis Traganitis and Georgios B. Giannakis, DM1015 Learning Dynamic User Interactions for Online Forum Commenting PredictionWu-Jiu Sun, Xiao Fan Liu, and Fei Shen, DM1023 DhakaNet: Unstructured Vehicle Detection using Limited Computational ResourcesTarik Reza Toha, Masfiqur Rahaman, Saiful Islam Salim, Mainul Hossain, Arif Mohamin Sadri, and A.

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