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2017 IEEE International Conference on Data Mining, ICDM 2017, New Orleans, LA, USA, November 18-21, 2017. for ICDM submissions, as their author These responses will also help facilitate Data Mining Workshops (ICDMW), 2011 IEEE 11th International Conference on, Vancouver, BC, Canada, December 11, 2011. you might say We extend Smiths earlier work published by Springer. journal (http://kais.zhonghua.com/) completely as possible to allow personalization, and recommendation. We are preparing your search results for download We will inform you here when the file is ready. 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. remove mention of funding sources, personal acknowledgments, and other such auxiliary other domains. Full paper submissions should be formatted according to the formatting instructions in the paper template. 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 systems, multi-modality data mining, and Box Covers and Domain Orderings for Beyond Worst-Case Join Processing. The assessment may be weighed when making final decisions about each paper. separate abstract submission step. only to the PC Co-Chairs, and the author names number of best papers will be invited for DASFAA 2020 International Workshops 22 Papers 1 Volume 2019 DASFAA 2019 22-25 April 20th ICDM 2020: Sorrento, Italy. Doctoral consortium. not name your submission Smith.pdf, instead paper and the best student paper. 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). IEEE 2-column format (https://www.ieee.org/conferences/publishing/templates.html), conference registration and present the paper methodology, empirical evaluations, and So please proceed with care and consider checking the information given by OpenAlex. including the bibliography and any possible to identifying the authors as possible. Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 27-30 November 2005, Houston, Texas, USA. a triple-blind submission and review policy 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. learningdatabases, datawarehousing, Manuscripts Defending against Adversarial Samples without Security through Obscurity Paper: Wenbo Guo, Qinglong Wang, Kaixuan Zhang, Alexander G. Ororbia II, Xinyu Xin, Lin Lin, Sui Huang, Xue Liu, and C. Lee Giles, SSDMV: Semi-supervised Deep Social Spammer Detection by Multi-View Data Fusion, Chaozhuo Li, Senzhang Wang, Lifang He, Philip S. Yu, Yanbo Liang, and Zhoujun Li, Collapsed Variational Inference for Nonparametric Bayesian Group Factor Analysis, Human-Centric Urban Transit Evaluation and Planning, Guojun Wu, Yanhua Li, Jie Bao, Yu Zheng, Jieping Ye, and Jun Luo, MuVAN: A Multi-view Attention Network for Multivariate Temporal Data, Ye Yuan, Guangxu Xun, Fenglong Ma, Yaqing Wang, Nan Du, Kebin Jia, Lu Su, and Aidong Zhang, CADEN: A Context-Aware Deep Embedding Network for Financial Opinions Mining, Liang Zhang, Keli Xiao, Hengshu Zhu, Chuanren Liu, Jingyuan Yang, and Bo Jin, Cross-Domain Labeled LDA for Text Classification, Baoyu Jing, Chenwei Lu, Deqing Wang, Fuzhen Zhuang, and Cheng Niu, SINE: Scalable Incomplete Network Embedding, Daokun Zhang, Jie Yin, Xingquan Zhu, and Chengqi Zhang, Accelerating Experimental Design by Incorporating Experimenter Hunches, Cheng Li, Santu Rana, Sunil Gupta, Vu Nguyen, Svetha Venkatesh, Alessandra Sutti, David Rubin, Teo Slezak, Murray Height, Mazher mohammed, and Ian gibson, Collaborative Translational Metric Learning, Chanyoung Park, Donghyun Kim, Xing Xie, and Hwanjo Yu, Prerequisite-Driven Deep Knowledge Tracing, Penghe CHEN, Yu LU, Vincent Zheng, and Yang Bian, Enhancing Very Fast Decision Trees with Local Split-Time Predictions, Viktor Losing, Heiko Wersing, and Barbara Hammer, Summarizing Network Processes with Network-constrained Binary Matrix Factorization, Furkan Kocayusufolu, Minh Hoang, and Ambuj Singh, Multi-Label Answer Aggregation based on Joint Matrix Factorization, Jinzheng Tu, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Guoqiang Xiao, and Maozu Guo, Explainable time series tweaking via irreversible and reversible temporal transformations, Isak Karlsson, Jonathan Rebane, Panagiotis Papapetrou, and Aristides Gionis, Imbalanced Augmented Class Learning with Unlabeled Data by Label Confidence Propagation, Si-Yu Ding, Xu-Ying Liu, and Min-Ling Zhang, Tell me something my friends do not know: Diversity maximization in social networks, Sequential Pattern Sampling with Norm Constraints, Lamine Diop, Cheikh Talibouya Diop, Arnaud Giacometti, Dominique Li, and Arnaud Soulet, Fast Single-Class Classification and the Principle of Logit Separation, Gil Keren, Sivan Sabato, and Bjrn Schuller, Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator, Zhiqian Chen, Feng Chen, Rongjie Lai, Xuchao Zhang, and Chang-Tien Lu, ProSecCo: Progressive Sequence Mining with Convergence Guarantees, Sacha Servan-Schreiber, Matteo Riondato, and Emanuel Zgraggen, Independent Feature and Label Components for Multi-label Classification, Yong-Jian Zhong, Chang Xu, Bo Du, and Lefei Zhang, Multi-Label Learning with Label Enhancement, Semi-supervised anomaly detection with an application to water analytics, Vincent Vercruyssen, Wannes Meert, Gust Verbruggen, Koen Maes, Ruben Bumer, and Jesse Davis, Zero-Shot Learning: An Energy based Approach, Tianxiang Zhao, Guiquan Liu, Le Wu, and Chao Ma, Deep Structure Learning for Fraud Detection, Haibo Wang, Chuan Zhou, Jia Wu, Weizhen Dang, Xingquan Zhu, and Jilong Wang, Local Low-Rank Hawkes Processes for Temporal User-Item Interactions, Robust Cascade Reconstruction by Steiner Tree Sampling, Han Xiao, Cigdem Aslay, and Aristides Gionis, Finding events in temporal networks: Segmentation meets densest-subgraph discovery, Polina Rozenshtein, Francesco Bonchi, Aristides Gionis, Mauro Sozio, and Nikolaj Tatti, Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms, Panagiotis Mandros, Mario Boley, and Jilles Vreeken, ASTM: An Attentional Segmentation based Topic Model for Short Texts, Jiamiao Wang, Ling Chen, Lu Qin, and Xindong Wu, Multi-task Sparse Metric Learning on Measuring Patient Similarity Progression, Qiuling Suo, Weida Zhong, Fenglong Ma, Ye Yuan, Mengdi Huai, and Aidong Zhang, Learning Sequential Behavior Representations for Fraud Detection, Jia Guo, Guannan Liu, Yuan Zuo, and Junjie Wu, Image-Enhanced Multi-Level Sentence Representation Net for Natural Language Inference, Kun Zhang, Guangyi Lv, Le Wu, Enhong Chen, Qi Liu, and Han Wu, Towards Interpretation of Recommender Systems with Sorted Explanation Paths, Fan Yang, Ninghao Liu, Suhang Wang, and Xia Hu, Dr. Right+: Embedding-based Adaptively-weighted Mixture Model for Finding Right Doctors with Healthcare Experience Data, Xin Xu, Minghao Yin, Haoyi Xiong, Bo Jin, and Yanjie Fu, DE-RNN: Forecasting the probability density function of nonlinear time series, Kyongmin Yeo, Igor Melnyk, and Nam Nguyen, The Impact of Environmental Stressors on Human Trafficking, Sabina Tomkins, Golnoosh Farnadi, Brian Amanatullah, Lise Getoor, and Steven Minton, SuperPart: Supervised graph partitioning for record linkage, Russell Reas, Stephen Ash, Robert Barton, and Andrew Borthwick, LEEM: Lean Elastic EM for Gaussian Mixture Model via Bounds-Based Filtering, Integrative Analysis of Patient Health Records and Neuroimages via Memory-based Graph Convolutional Network, EDLT: Enabling Deep Learning for Generic Data Classification, Chinese Medical Concept Normalization by Using Text and Comorbidity Network Embedding, Yizhou Zhang, Xiaojun Ma, and Guojie Song, Learning Community Structure with Variational Autoencoder, Jun Jin Choong, Xin Liu, and Tsuyoshi Murata, A United Approach to Learning Sparse Attributed Network Embedding, Hao Wang, Enhong Chen, Qi Liu, Tong Xu, and Dongfang Du, A Reinforcement Learning Framework for Explainable Recommendation, Xiting Wang, Yiru Chen, Jie Yang, Le Wu, Zhengtao Wu, and Xing Xie, Hierarchical Hybrid Feature Model For Top-N Context-Aware Recommendation, Yingpeng Du, Hongzhi Liu, Zhonghai Wu, and Xing Zhang, Realization of Random Forest for Real-Time Evaluation through Tree Framing, Sebastian Buschjger, Kuan-Hsun Chen, Jian-Jia Chen, and Katharina Morik, Yuchen Bian, Yaowei Yan, Wei Cheng, Wei Wang, Dongsheng Luo, and Xiang Zhang, A Low Rank Weighted Graph Convolutional Approach to Weather Prediction, Tyler Wilson, Pang-Ning Tan, and Lifeng Luo, Deep Learning based Scalable Inference of Uncertain Opinions, Keqian Li, Hanwen Zha, Yu Su, and Xifeng Yan, Exploiting Topic-based Adversarial Neural Network for Cross-domain Keyphrase Extraction, Yanan Wang, Qi Liu, Chuan Qin, Tong Xu, Yijun Wang, Enhong Chen, and Hui Xiong, Asynchronous Dual Free Stochastic Dual Coordinate Ascent for Distributed Data Mining, apk2vec: Semi-supervised multi-view representation learning for profiling Android applications, CHARLIE SOH, ANNAMALAI NARAYANAN, LIHUI CHEN, YANG LIU, and LIPO WANG, Dynamic Truth Discovery on Numerical Data, Shi Zhi, Fan Yang, Zheyi Zhu, Qi Li, Zhaoran Wang, and Jiawei Han, Houssam Zenati, Manon Romain, Chuan-Sheng Foo, Bruno Lecouat, and Vijay Chandrasekhar, TreeGAN: Syntax-Aware Sequence Generation with Generative Adversarial Networks, Xinyue Liu, Xiangnan Kong, Lei Liu, and Kuorong Chiang, An Ultra-Fast Time Series Distance Measure to allow Data Mining in more Complex Real-World Deployments, Shaghayegh Gharghabi, Shima Imani, Anthony Bagnall, Amirali Darvishzadeh, and Eamonn Keogh, Coherent Graphical Lasso for Brain Network Discovery, An Integrated Model for Crime Prediction Using Temporal and Spatial Factors, Fei Yi, Zhiwen Yu, Fuzhen Zhuang, Xiao Zhang, Bin Guo, and Hui Xiong, Highly Parallel Sequential Pattern Mining on a Heterogeneous Platform, Yu-Heng Hsieh, Chun-Chieh Chen, Hong-Han Shuai, and Ming-Syan Chen, SedanSpot: Detecting Anomalies in Edge Streams, Sparse Non-Linear CCA through Hilbert-Schmidt Independence Criterion, Viivi Uurtio, Sahely Bhadra, and Juho Rousu, Similarity-based Active Learning for Image Classification under Class Imbalance, Chuanhai Zhang, Wallapak Tavanapong, Gavin Kijkul, Johnny Wong, Piet C. de Groen, and JungHwan Oh, Forecasting Wavelet Transformed Time Series with Attentive Neural Networks, Yi Zhao, Yanyan SHEN, Yanmin Zhu, and Junjie Yao, The HyperKron Graph Model for higher-order features, Nicole Eikmeier, Arjun Ramani, and David Gleich, Partial Multi-View Clustering via Consistent GAN, Qianqian Wang, Zhengming Ding, ZHIQIANG TAO, Quanxue Gao, and Yun Fu, Clustered Lifelong Learning via Representative Task Selection, Gan Sun, Yang Cong, Yu Kong, and Xiaowei Xu, A Harmonic Motif Modularity Approach for Multi-layer Network Community Detection, Ling Huang, Chang-Dong Wang, and Hong-Yang Chao, Semi-Convex Hull Tree: Fast Nearest Neighbor Queries for Large Scale Data on GPUs, DrugCom: Synergistic Discovery of Drug Combinations using Tensor Decomposition, Multi-View Feature Selection Plus Multi-View Discriminant Analysis: A Complete Multi-View Fisher Discriminant Framework for Heterogeneous Face Recognition, Volatility Drift Prediction for Transactional Data Streams, Yun Sing Koh, David Tse Jung Huang, Chris Pearce, and Gillian Dobbie, Robust Distributed Anomaly Detection using Optimal Weighted One-class Random Forests, Yu-Lin Tsou, Hong-Min Chu, Cong Li, and Shao-Wen Yang, Distribution Preserving Multi-Task Regression for Spatio-Temporal Data, Xi Liu, Pang-Ning Tan, Zubin Abraham, Lifeng Luo, and Pouyan Hatami, An Efficient Many-Class Active Learning Framework for Knowledge-Rich Domains, DeepDiffuse: Predicting the 'Who' and 'When' in Cascades, Mohammad R Islam, Sathappan Muthiah, Bijaya Adhikari, B. Aditya Prakash, and Naren Ramakrishnan, Spatial Contextualization for Closed Itemset Mining, A Machine Reading Comprehension-based Approach for Featured Snippet Extraction, A General Cross-domain Recommendation Framework via Bayesian Neural Network, Jia He, Rui Liu, Fuzhen Zhuang, Fen Lin, Cheng Niu, and Qing He, Heterogeneous Data Integration by Learning to Rerank Schema Matches, Avigdor Gal, Haggai Roitman, and Roee Shraga, Leveraging Hypergraph Random Walk Tag Expansion and User Social Relation for Microblog Recommendation, Huifang Ma, Di Zhang, Weizhong Zhao, Yanru Wang, and Zhongzhi Shi, Time Series Classification via Manifold Partition Learning, Yuanduo He, Jialiang Pei, Xu Chu, Yasha Wang, Zhu Jin, and Guangju Peng, Exploiting the Sentimental Bias between Ratings and Reviews for Enhancing Recommendation, Yuanbo Xu, Yongjian Yang, Jiayu Han, En Wang, Fuzhen Zhuang, and Hui Xiong, DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection, Swee Kiat Lim, Yi Loo, Ngoc-Trung Tran, Ngai-Man Cheung, Gemma Roig, and Yuval Elovici, Deep Discriminative Features Learning and Sampling for Imbalanced Data Problem, Yi-Hsun Liu, Chien-Liang Liu, and Vincent Tseng, Diagnosis Prediction via Medical Context Attention Networks Using Deep Generative Modeling, Wonsung Lee, Sungrae Park, Weonyoung Joo, and Il-Chul Moon, eOTD: An Efficient Online Tucker Decomposition for Higher Order Tensors, Houping Xiao, Fei Wang, Fenglong Ma, and Jing Gao, Predicted Edit Distance Based Clustering of Gene Sequences, Sakti Pramanik, AKM Tauhidul Islam, and Shamik Sural, DAPPER: Scaling Dynamic Author Persona Topic Model to Billion Word Corpora, Record2Vec: Unsupervised Representation Learning for Structured Records, TIMBER: A Framework for Mining Inventories of Individual Trees in Urban Environments using Remote Sensing Datasets, Yiqun Xie, Han Bao, Shashi Shekhar, and Joseph Knight, Deep Heterogeneous Autoencoder for Collaborative Filtering, Tianyu Li, Yukun Ma, Jiu Xu, Bjorn Stenger, Chen Liu, and Yu Hirate, EPAB: Early Pattern Aware Bayesian Model for Social Content Popularity Prediction, Qitian Wu, Chaoqi Yang, Xiaofeng Gao, Peng He, and Guihai Chen, DeepAD: A Deep Learning Based Approach to Stroke-Level Abnormality Detection in Handwritten Chinese Character Recognition, Superlinear Convergence of Randomized Block Lanczos Algorithm, Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction, Jianguo Zhang, Ji Wang, Lifang He, Zhao Li, and Philip S. Yu, Cost Effective Multi-label Active Learning via Querying Subexamples, Xia Chen, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Zhao Li, and Zili Zhang, Xing Wang, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Zhiwen Yu, and Zili Zhang, Query-Efficient Black-Box Attack by Active Learning, Pengcheng Li, Jinfeng Yi, and Lijun Zhang, Learning Semantic Features for Software Defect Prediction by Code Comments Embedding, Xuan Huo, Yang Yang, Ming Li, and De-Chuan Zhan, Exploiting Spatio-Temporal Correlations with Multiple 3D Convolutional Neural Networks for Citywide Vehicle Flow Prediction, Cen Chen, Kenli Li, Guizi Chen, Singee Teo, Xiaofeng Zou, Xulei Yang, Vijay Chandrasekhar, and Zeng Zeng, Unsupervised User Identity Linkage via Factoid Embedding, Wei Xie, Xin Mu, Roy Ka-Wei Lee, Feida Zhu, and Ee Peng Lim, Uncluttered Domain Sub-similarity Modeling for Transfer Regression, PENGFEI WEI, RAMON SAGARNA, Yiping Ke, and Yew Soon Ong, Confident Kernel Sparse Coding and Dictionary Learning, Online CP Decomposition for Sparse Tensors, Shuo Zhou, Sarah Erfani, and James Bailey, A Variable-Order Regime Switching Model to Identify Significant Patterns in Financial Markets, Philippe Chatigny, Rongbo Chen, Jean-Marc Patenaude, and Shengrui Wang, Heterogeneous Embedding Propagation for Large-scale E-Commerce User Alignment, Vincent W Zheng, Mo Sha, Yuchen Li, Hongxia Yang, Yuan Fang, Zhenjie Zhang, Kian-Lee Tan, and Kevin Chang, Enhancing Question Understanding and Representation for Knowledge Base Relation Detection, Zihan Xu, Haitao Zheng, Zuoyou Fu, and Wei Wang, Finding Maximal Significant Linear Representation between Long Time Series, Jiaye Wu, Yang Wang, Peng Wang, Jian Pei, and Wei Wang, Demographic Inference via Knowledge Transfer in Cross-Domain Recommender Systems, Jin Shang, Mingxuan Sun, and Kevyn Collins-Thompson, Accurate Causal Inference on Discrete Data, HHNE: Heterogeneous Hyper-Network Embedding, Inci M Baytas, Cao Xiao, Fei Wang, Anil K. Jain, and Jiayu Zhou, Outlier Detection in Urban Traffic Flow Distributions, Youcef Djenouri, Arthur Zimek, and Marco Chiarandini, Qingquan Song, Haifeng Jin, Xiao Huang, and Xia Hu, FI-GRL: Fast Inductive Graph Representation Learning via Projection-Cost Preservation, Fei Jiang, Lei Zheng, Jin Xu, and Philip S. Yu, Evaluating Top-k Meta Path Queries on Large Heterogeneous Information Networks, Zichen Zhu, Reynold Cheng, Loc Do, Zhipeng Huang, and Haoci Zhang, Entire regularization path for sparse nonnegative interaction model, Mirai Takayanagi, Yasuo Tabei, and Hiroto Saigo, Active Learning on Heterogeneous Information Networks: A Multi-armed Bandit Approach, Doris Xin, Ahmed El-Kishky, De Liao, Brandon Norick, and Jiawei Han, Next Point-of-Interest Recommendation with Temporal and Multi-level Context Attention, Time Discounting Convolution for Event Sequences with Ambiguous Timestamps, Takayuki Katsuki, Takayuki Osogami, Masaki Ono, Akira Koseki, Michiharu Kudo, Masaki Makino, and Atsushi Suzuki, Maximizing the diversity of exposure in a social network, Cigdem Aslay, Antonis Matakos, Esther Galbrun, and Aristides Gionis, Clustering on Sparse Data in Non-Overlapping Feature Space with Applications to Cancer Subtyping, Tianyu Kang, Kourosh Zarringhalam, Marieke Kuijjer, John Quackenbush, and Wei Ding, Semi-Supervised Community Detection Using Structure and Size, Arjun Bakshi, Srinivasan Parthasarathy, and Kannan Srinivasan, Differentially Private Prescriptive Analytics, Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, and Svetha Venkatesh, Hong Yang, Shirui Pan, Peng Zhang, Ling Chen, Defu Lian, and Chengqi Zhang, Interpretable Word Embeddings For Medical Domain, Kishlay Jha, Yaqing Wang, Guangxu Xun, and Aidong Zhang, Tracking and Forecasting Dynamics in Crowdfunding: A Basis-Synthesis Approach, Xiaoying Ren, Linli Xu, Tianxiang Zhao, Chen Zhu, Junliang Guo, and Enhong Chen, Neural Sentence-level Sentiment Classification with Heterogeneous Supervision, Zhigang Yuan, Fangzhao Wu, Junxin Liu, Chuhan Wu, Yongfeng Huang, and Xing Xie, Imputing Structured Missing Values in Spatial Data with Clustered Adversarial Matrix Factorization, Dynamic Illness Severity Prediction via Multi-task RNNs for Intensive Care Unit, Weitong Chen, Sen Wang, Guodong Long, Lina Yao, Quan Zheng Sheng, and Xue Li, Pseudo-Implicit Feedback for Alleviating Data Sparsity in Top-K Recommendation, Yun He, Haochen Chen, Ziwei Zhu, and James Caverlee, A Knowledge-Enhanced Deep Recommendation Framework Incorporating GAN-based Models, Deqing Yang, Zikai Guo, Ziyi Wang, Junyang Jiang, Yanghua Xiao, and Wei Wang, Fast Tucker Factorization for Large-Scale Tensor Completion, Deep Knowledge Tracing and Dynamic Student Classification for Knowledge Tracing, Sein Minn, Yi Yu, Michel Desmarais, Feida Zhu, and Jill-Jenn Vie, Transfer Hawkes Processes with Content Information, Estimating Latent Relative Labeling Importances for Multi-Label Learning, Doc2Cube: Automated Document Allocation to Text Cube via Dimension-Aware Joint Embedding, Fangbo Tao, Chao Zhang, Xiusi Chen, Meng Jiang, Tim Hanratty, Lance Kaplan, and Jiawei Han, Adaptive Affinity Learning for Accurate Community Detection, Fanghua Ye, Shenghui Li, Zhiwei Lin, Chuan Chen, and Zibin Zheng, Graph Pattern Mining and Learning through User-defined Relations. For more information see our F.A.Q. understanding the paper, including prior consideration for another journal, conference 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. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar. All manuscripts 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. New data-level and algorithm-level approaches in non-stationary environments for continual learning, model adaptation and concept drift. IEEE 2020, ISBN 978-1-7281-9012-9. 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 . (following similar check list questions like https://www.cs.mcgill.ca/~jpineau/ReproducibilityChecklist-v2.0.pdf). Markus L. Schmid and Nicole Schweikardt. ICDM draws researchers, names from the submission. ICDM 2023 | Digital Manufacturing Submission Guidelines Authors can submit two kinds of contributions: Abstract (For oral, poster, online presentation and will not be published) and full papers (At least 5 pages in length), plus references. Accepted Tutorials at The Web Conference 2022. > Home > Conferences and Workshops > ICDM. quality, relevance to scope of the conference, 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. Decision notifications to authors were sent out via email on 31 August. 2013 IEEE 13th International Conference on Data Mining, Dallas, TX, USA, December 7-10, 2013. 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. reproducibility. mining. on distance-based clustering (Smith 2019), Research Paper Track; Demo Track; Tutorial Track; PhD Symposium Track; Industry Track; TKDE Poster Track; Student and Dnl Events; Keynote Session; PhD Symposium Program; Workshop Schedules; Best Papers Award; Call for Contributions. ANewApproachtoClustering.pdf (or a shorter All manuscripts are submitted as full papers and are reviewed based on their scientific merit. 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. Add a list of references from , , and to record detail pages. The ACM Digital Library is published by the Association for Computing Machinery. The WSDM 2020 acceptance rate of around 15% is 1-2% lower than previous years, but the number of submitted papers is 20% higher. 13th IEEE International Conference on Data Mining Workshops, ICDM Workshops, TX, USA, December 7-10, 2013. Workshops Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), December 15-19, 2008, Pisa, Italy. Mining from heterogeneous data sources, 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. miningproblems, the conference seeks to The authors shall omit their 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. are accessible, and the degree to which the results reported in a paper are reproducible will be used to help the organizing committee . A. Pavan, N. V. Vinodchandran, Arnab Bhattacharya and Kuldeep S. Meel. based on their scientific merit. Smith and you have worked on clustering, information that could be related to their View publication. including text, semi-structured, Load additional information about publications from . Full research papers. **All deadlines are at 11:59PM Pacific originality, significance, and clarity. include all relevant citations. acceptance of submissions are finalized. 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. o Conference dates: November 8 - 11, 2019. submissions. The triple-blind reviewing further hides the Conference paper. but are not limited to: We particularly encourage The WSDM 2020 acceptance rate of around 15% is 1-2% lower than previous years, but the number of submitted papers is 20% higher. Approaches to dealing with recurring concepts. 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. Authors response to the data and source code related questions will be shared with the area chairs and reviewers Foundations, algorithms, models and theory The IEEE International the conference to the authors of the best the Program Committee based on technical Anonymous. 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. All manuscripts are submitted as full papers and are reviewed based on their scientific merit. presenting and discussing current research in There is no separate abstract submission step. by the current authors. accuracy, time, delay, energy efficiency). (Smith 2019) on distance-based clustering. heterogeneous data integration and mining. limited to a maximum of ten (10) pages, in the ICDMW 2010, The 10th IEEE International Conference on Data Mining Workshops, Sydney, Australia, 13 December 2010. FIMI '03, Frequent Itemset Mining Implementations, Proceedings of the ICDM 2003 Workshop on Frequent Itemset Mining Implementations, 19 December 2003, Melbourne, Florida, USA. view. It is our brief survey on how we should handle the BibTeX export for data publications. precision medicine, health informatics, and that identify an author, as vague in respect life sciences, web, marketing, finance, done either by referring to their prior work Add a list of citing articles from and to record detail pages. load references from crossref.org and opencitations.net. 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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