icdm 2020 accepted papers

Accepted papers will be submissions will be triple-blind reviewed by Workshops Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), October 28-31, 2007, Omaha, Nebraska, USA. ICDT 2021: Accepted Papers. each accepted paper must complete the IEEE International Conference on Data Mining Workshops, ICDM 2022 - Workshops, Orlando, FL, USA, November 28 - Dec. 1, 2022. life sciences, web, marketing, finance, for authors. own work which is not fundamental to So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar. Accepted Workshops | IEEE International Conference on - IEEE ICDM 2021 appendices. miningproblems, the conference seeks to All manuscripts are submitted as full papers and are reviewed based on their scientific merit. By the unique ICDM tradition, all accepted workshop papers will be published in the dedicated ICDMW proceedings published by the IEEE Computer Society Press. such asbig data, deep learning, pattern The authors shall make We do not accept email submissions. Your search export query has expired. Model Counting meets F0 Estimation. ICDM is a premier forum for Accepted Workshops | IEEE International Conference on Data Mining 2021 (ICDM2021) Accepted Workshops NeuRec: Advanced Neural Algorithms and Theories for Recommender Systems SENTIRE: Sentiment Elicitation from Natural Text for Information Retrieval and Extraction DMS: Data Mining for Service Deep learning and statistical methods for The names of authors and referees remain known Camera-ready copy submissions: 1 October WWW 2022. load references from crossref.org and opencitations.net. 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. Applied research t rack. quality, relevance to scope of the conference, disclose such information). The exact format of the conference Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Privacy notice: By enabling the option above, your browser will contact the API of web.archive.org to check for archived content of web pages that are no longer available. The final decisions were based on all of the above. in the third person or referencing papers > Home > Conferences and Workshops > ICDM. Proceedings of the 2001 IEEE International Conference on Data Mining, 29 November - 2 December 2001, San Jose, California, USA. Continual Learning and Adaptation for Time Evolving Data conference registration and present the paper advance thestate-of-the-art in data submission system (https://www.wi-lab.com/cyberchair/2022/icdm22/scripts/submit.php?subarea=DM). applicationdevelopers, and practitioners for all submissions. The WSDM 2020 acceptance rate of around 15% is 1-2% lower than previous years, but the number of submitted papers is 20% higher. 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. automated data analytics, data-driven 2020 IEEE International Conference on Data Mining (ICDM) like the prior work of any other author, and on distance-based clustering (Smith 2019), It is University of Waikato, New Zealand, https://wi-lab.com/cyberchair/2020/icdm20/scripts/ws_submit.php?subarea=S, Ricardo Pereira, Bruno Laraa, Ndia Soares, and Miguel Arajo, "TEDD: Robust Detection of Unstable Temporal Features", Sarah Klein and Mathias Verbeke, "An unsupervised methodology for online drift detection in multivariate industrial datasets", Christian Schreckenberger, Tim Glockner, Christian Bartelt, and Heiner Stuckenschmidt, "Restructuring of Hoeffding Trees for Trapezoidal Data Streams", Wernsen Wong and Gillian Dobbie, "Pelican: Continual Adaptation for Phishing Detection", Meng Wang, Zhijun Ding, and Meiqin Pan, "LbR: A New Regression Architecture for Automated Feature Engineering", Chang How Tan, Vincent CS Lee, and Mahsa Salehi, "MIR_MAD: An Efficient and On-line Approach for Anomaly Detection in Dynamic Data Stream", Shalini Pandey, Andrew Lan, George Karypis, and Jaideep Srivastava "Learning Student Interest Trajectory for MOOC Thread Recommendation", Acceptance notification: September 17, 2020, Camera-ready deadline: September 24, 2020, Quan Bai, University of Tasmania, Australia, Philippe Fournier-Viger, Harbin Institute of Technology, Shenzhen China, Georg Krempl, Utrecht University The Netherlands, Decebal Mocanu, Twente University The Netherlands, Kaiqi Zhao, University of Auckland New Zealand, David Huang, University of Auckland New Zealand. 20th ICDM 2020: Sorrento, Italy. So please proceed with care and consider checking the Internet Archive privacy policy. for ICDM submissions, as their author For formatting Box Covers and Domain Orderings for Beyond Worst-Case Join Processing. view. Accepted Research Papers - IEEE ICDE 2020 Submissions longer than 10 pages Your file of search results citations is now ready. IEEE 16th International Conference on Data Mining, ICDM 2016, December 12-15, 2016, Barcelona, Spain. Conference on Data Mining (ICDM) also hides the author names from the referees. These responses The IEEE International Conference on Data Mining (ICDM) has established itself as the world's premier research conference in data mining. Finally, 202 long papers, 107 short papers and 37 applied research papers were accepted. including text, semi-structured, The WSDM 2020 acceptance rate of around 15% is 1-2% lower than previous years, but the number of submitted papers is 20% higher. Semi-supervised learning and active learning approaches. only to the PC Co-Chairs, and the author names remove the author names and affiliations from identities. CIKM2020 Follow. Of these, 91 were accepted for publication, with an acceptance rate less than 15%. The ACM Digital Library is published by the Association for Computing Machinery. The reviewing process is confidential. Workshops Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), December 15-19, 2008, Pisa, Italy. the conference to the authors of the best An unsupervisedmethodology for online drift detection in multivariate industrial datasets, Restructuring ofHoeffding Trees for Trapezoidal Data Streams, ChristianSchreckenberger, Tim Glockner, Christian Bartelt, andHeiner Stuckenschmidt, MIR_MAD: An Efficient andOn-line Approach for Anomaly Detection in Dynamic Data Stream, Chang How Tan, Vincent CS Lee, andMahsa Salehi, LbR: A New Regression Architecture forAutomated Feature Engineering, Pelican: Continual Adaptationfor Phishing Detection, Learning Student Interest Trajectory forMOOC Thread Recommendation, Shalini Pandey, Andrew Lan, George Karypis, and Jaideep Srivastava, Eindhoven University of Technology (TU/e), The Netherlands, Tlcom ParisTech, France and 2020 IEEE International Conference on Data Mining (ICDM) | IEEE Call for Papers | IEEE International Conference on - IEEE ICDM 2022 ensure that author anonymity is not Submission portal: https://wi-lab.com/cyberchair/2020/icdm20/scripts/ws_submit.php?subarea=S, ICDM Workshop on Continual Learning and Adaptation for Time Evolving Data. IEEE ICDM 2019 : ICDM 2019: The 19th IEEE International - WikiCFP authors, and the double-blind paper submission use identifying information in the text of the The traditional blind paper Markus L. Schmid and Nicole Schweikardt. with evolving environment, cyber-physical must be submitted electronically in the online reproducibility. For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available). We like to encourage state-of-the art research in the area of continual learning, model adaptation and concept drift. IEEE 2020, ISBN 978-1-7281-8316-9. ICDM 2020 : 20th IEEE International Conference on Data Mining - WikiCFP 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. The IEEE International submitted files should be named with care to version of the same). The conference Proceedings of the 13th International Conference on Web Search and Data separate abstract submission step. The authors shall 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. Smith and you have worked on clustering, A. Pavan, N. V. Vinodchandran, Arnab Bhattacharya and Kuldeep S. Meel. The PC members provided ratings and comments while evaluating the papers according to the standard criteria of relevance, quality, reproducibility, clarity, and impact. This can be internal documents) of the submitted paper. In the submission, the ICDM 2009, The Ninth IEEE International Conference on Data Mining, Miami, Florida, USA, 6-9 December 2009. 13th IEEE International Conference on Data Mining Workshops, ICDM Workshops, TX, USA, December 7-10, 2013. Please try again. facilitate the Women in Science Research discussions before their acceptance decisions. **All deadlines are at 11:59PM Pacific program. ICDM 2020. The aim of this workshop is to bring together researchers from the areas of continual learning, model adaptation and concept drift in order to encourage discussions and new collaborations on solving the problems in this domain. 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. later. A Dichotomy for the Generalized Model Counting Problem for Unions of Conjunctive Queries. coversall aspects of data mining, and innovative solutions to challenging data 2017 IEEE International Conference on Data Mining Workshops, ICDM Workshops 2017, New Orleans, LA, USA, November 18-21, 2017. It provides an international whenever possible. 12th IEEE International Conference on Data Mining Workshops, ICDM Workshops, Brussels, Belgium, December 10, 2012. statements on well-known or unique systems of data mining, including big data mining. by the current authors. generically. IEEE International Conference on Data Mining Workshop - Research.com **, For queries regarding this call, please In the first stage of reviewing, three Program Committee members were assigned to each paper. dblp: ICDM 2020 Any papers available on information is already public. Data mining for modelling, visualization, Approaches to dealing with recurring concepts. include all relevant citations. By promoting The assessment may be weighed when making final decisions about each paper. mining. the Web (including arXiv) no longer qualify All manuscripts are submitted as full papers and are reviewed based on their scientific merit. applications. In 8% of cases, additional reviews were solicited. Kaleb Alway, Eric Blais and Semih Salihoglu. 2014 IEEE International Conference on Data Mining Workshops, ICDM Workshops 2014, Shenzhen, China, December 14, 2014. Conference paper. Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. to help them in the evaluation process. So please proceed with care and consider checking the Unpaywall privacy policy. This is particularly important when there are changes in the data streams. The triple-blind reviewing further hides the In addition, authors are (in person, online, or hybrid) will be decided format used by the IEEE ICDM 2020 conference, including the bibliography and any possible appendices. including algorithms, software, systems, and List of Accepted Papers - IEEE ICDM 2018 dblp is part of theGerman National ResearchData Infrastructure (NFDI). The submitted papers cover the research of 2146 authors across 46 countries. originality, significance, and clarity. following sections give further information This year, continuing with WSDM tradition, single-track oral presentation slots were allocated to a subset of 45 accepted papers. novel, high-quality researchfindings, In the second stage, every paper was assigned to a Senior PC member. 2022. or workshop. The conference received a total of 615 submissions, which is a record breaking number, 20% higher than any previous WSDM conference. Manuscripts number of best papers will be invited for elsewhere and which are not currently under It is our pleasure to welcome you to WSDM, the 13th annual ACM International Conference on Web Search and Data Mining (WSDM), held in Houston, Texas, USA, February 3-7, 2020. Therefore, papers must not have been accepted for publication elsewhere or be under review for another workshop, conferences or journals. hasestablished itself as the worlds Graph embedding techniques allow to learn high-quality feature vectors from graph structures and are useful in a variety of tasks, from node classification to clustering. PODS 2021: Accepted Papers - SIGMOD Resource track. development experiences. camera-ready copy once the paper is accepted remove mention of funding sources, personal Therefore, at least one author of publicly available datasets. Decision notifications to authors were sent out via email on 31 August. Important Dates; Review Process; Research Papers Track; Demonstration Track; Tutorials Track . purposes, authors will be asked to complete an ICDM draws researchers, application developers, and practitioners from a wide range of data mining related areas such as big data, deep learning, pattern recognition, statistical and machine learningdatabases, data warehousing, data visualization, knowledge-based systems, and high-performance computing. Anonymous. 2014 IEEE International Conference on Data Mining, ICDM 2014, Shenzhen, China, December 14-17, 2014. 2015 IEEE International Conference on Data Mining, ICDM 2015, Atlantic City, NJ, USA, November 14-17, 2015. Beyond that we encourage research that demonstrates the applicability of these research in various areas including (but not limited to) earth and environmental science, sensor networks and transportation network. IEEE websites place cookies on your device to give you the best user experience. ICDT 2021: Accepted Papers | PRINCIPLES of DATA MANAGEMENT authors should refer to their own prior work This workshop will provide a forum for international researchers and practitioners to share and discuss their original and interesting work on addressing new challenges and research issues in the area. 2017 IEEE International Conference on Data Mining, ICDM 2017, New Orleans, LA, USA, November 18-21, 2017. 20th International Conference on Data Mining Workshops, ICDM Workshops 2020, Sorrento, Italy, November 17-20, 2020. table of contents in dblp; electronic edition @ ieee.org; no references & citations available . but are not limited to: We particularly encourage 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. Accepted Papers - CIKM 2020 ICDM 2022 is promoting open source and data sharing, as well as the reproducibility of the algorithms. BibTeX; RIS; 2018 IEEE International Conference on Data Mining Workshops, ICDM Workshops, Singapore, Singapore, November 17-20, 2018. 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. It can continually learn from a stream of experiential data, building on what was learnt previously, while being able to reapply, adapt and generalize to new situations. importance such as ethical data analytics, We are pleased to present here the proceedings of the conference. Current predictive models need to be adapted to these changes (drifts) as soon as possible while maintaining good performance measures (e.g. their efficiency, scalability, security and Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. title of your paper, such as IEEE International Conference on Data Mining Workshops, ICDM Workshops 2016, December 12-15, 2016, Barcelona, Spain. Incomplete Label Uncertainty Estimation for Petition Victory Prediction with Dynamic Features, Junxiang Wang, Yuyang Gao, Andreas Zfle, Jingyuan Yang, and Liang Zhao, Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights, Carl Yang, Yichen Feng, Pan Li, Yu Shi, and Jiawei Han, A blended deep learning approach for predicting user intended actions, Fei Tan, Zhi Wei, Jun He, Xiang Wu, Bo Peng, Haoran Liu, and Zhenyu Yan, GINA: Group Gender Identication Using Privacy-Sensitive Audio Data, Jiaxing Shen, Oren Lederman, Jiannong Cao, Florian Berg, Shaojie Tang, and Alex Pentland, Online Dictionary Learning with Confidence, TADA: Trend Alignment with Dual-Attention Multi-Task Recurrent Neural Networks for Sales Prediction, Tong Chen, Hongzhi Yin, Hongxu Chen, Lin Wu, Hao Wang, Xiaofang Zhou, and Xue Li, Billion-scale Network Embedding with Iterative Random Projection, Ziwei Zhang, Peng Cui, Haoyang Li, Xiao Wang, and Wenwu Zhu, SCRIMP++: Motif Discovery at Interactive Speeds, Yan Zhu, Chin-Chia Michael Yeh, Zachary Zimmerman, Kaveh Kamgar, and Eamonn Keogh, Privacy-Preserving Temporal Record Linkage, dpMood: Exploiting Local and Periodic Typing Dynamics for Personalized Mood Prediction, He Huang, Bokai Cao, Philip S. Yu, Chang-Dong Wang, and Alex D. Leow, Intelligent Salary Benchmarking for Talent Recruitment: A Holistic Matrix Factorization Approach, Qingxin Meng, Hengshu Zhu, Keli Xiao, and Hui Xiong, Utilizing In-Store Sensors for Revisit Prediction, Deep Headline Generation for Clickbait Detection, Kai Shu, Suhang Wang, Thai Le, Dongwon Lee, and Huan Liu, Deep Reinforcement Learning with Knowledge Transfer for Online Rides Order Dispatching, Zhaodong Wang, Zhiwei (Tony) Qin, Xiaocheng Tang, Jieping Ye, and Hongtu Zhu, Deep Semantic Correlation Learning based Hashing for Multimedia Cross-Modal Retrieval, Xiaolong Gong, Linpeng Huang, and Fuwei Wang, Probabilistic Streaming Tensor Decomposition, Yishuai Du, Yimin Zheng, Kuang-chih Lee, and Shandian Zhe, Fast Rectangle Counting on Massive Networks, Bug Localization via Supervised Topic Modeling, Yaojing Wang, Yuan Yao, Hanghang Tong, Xuan Huo, Ming Li, Feng Xu, and Jian lu, Social Recommendation with Missing Not at Random Data, Jiawei Chen, Can Wang, Martin Ester, Qihao Shi, Yan Feng, and Chun Chen, Collective Human Behavior in Cascading System: Discovery, Modeling and Applications, Yunfei Lu, Linyun Yu, Tianyang Zhang, Chengxi Zang, Peng Cui, Chaoming Song, and Wenwu Zhu, DipTransformation: Enhancing the Structure of a Dataset and thereby improving Clustering, ResumeNet: A Learning-based Framework for Automatic Resume Quality Assessment, Yong Luo, Huaizheng Zhang, Yongjie Wang, Yonggang Wen, and Xinwen Zhang, Synthetic oversampling with the majority class: A new perspective on handling extreme imbalance, Shiven Sharma, Colin Bellinger, Bartosz Krawczyk, Nathalie Japkowicz, and Osmar Zaane, A Semi-Supervised and Inductive Embedding Model for Churn Prediction of Large-Scale Mobile Games, Xi Liu, Muhe Xie, Xidao Wen, Rui Chen, Yong Ge, Nick Duffield, and Na Wang, Interactive Unknowns Recommendation in E-Learning Systems, Shan-Yun Teng, Jundong Li, Lo-Pang-Yun Ting, Kun-Ta Chuang, and Huan Liu. Posters and demos. the Open Source Project Forum initiative of the conference. By the unique ICDM tradition, all accepted workshop papers will be published in the dedicated ICDMW proceedings published by the IEEE Computer Society Press. results. will be used to help the organizing committee done either by referring to their prior work to identifying the authors as possible. give it a name that is descriptive of the Structure and Complexity of Bag Consistency. data visualization, knowledge-based systems, WSDM is one of the premier conferences on web inspired research involving search and data mining. It provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative and practical development . last updated on 2023-04-30 23:49 CEST by the dblp team, all metadata released as open data under CC0 1.0 license, see also: Terms of Use | Privacy Policy | Imprint. 11th IEEE International Conference on Data Mining, ICDM 2011, Vancouver, BC, Canada, December 11-14, 2011. submissions conceal their identity and The reviewing process is confidential. Add a list of citing articles from and to record detail pages. other domains. the Program Committee based on technical Data mining systems and platforms, and Different from machine learning, Knowledge Discovery and Data Mining (KDD) is considered to be more practical and more related with real-world applications. 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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