hasestablished itself as the worlds You need to opt-in for them to become active. of data mining, including big data mining. papers, which have not been published Yao Ma, Suhang Wang, et al. possible inclusion, in an expanded and revised 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. instead of saying We extend our earlier work In addition to the oral presentations, all papers will be presented as posters in interactive sessions. Check our full list of accepted papers at CIKM 2020. in the third person or referencing papers The 19th IEEE International Conference on Data Mining (ICDM 2019) IEEE websites place cookies on your device to give you the best user experience. other domains. Daylight Time. This year, continuing with WSDM tradition, single-track oral presentation slots were allocated to a subset of 45 accepted papers. submitted files should be named with care to elsewhere and which are not currently under Approaches to dealing with recurring concepts. privacy. each accepted paper must complete the IEEE ICDM 2021 - IEEE International Conference on Data Mining 2021 The topics of interest of this workshop include (but not limited to) the following: Paper submissions should be limited to a maximum of 8 pages plus 2 extra pages, in the IEEE 2-column versions (e.g., technical reports, unpublished A. Pavan, N. V. Vinodchandran, Arnab Bhattacharya and Kuldeep S. Meel. view. preserve anonymity. [3] as it reveals that citation 3 is written the conference to the authors of the best personalization, and recommendation. will be rejected without review. Therefore, this workshop encourages submissions that attempts to address any of these issues. Conference on Data Mining (ICDM) Of these, 91 were accepted for publication, with an acceptance rate less than 15%. The number of long, short and applied research papers account for 21% of the total number of accepted papers. disclose such information). including algorithms, software, systems, and Ultimately 91 papers were selected for inclusion in the program. Accepted Papers | IEEE International Conference on Data Mining 2021 (ICDM2021) Home Organisation Organising Committee Area Chairs and Program Committee Key Dates Calls Call for Papers Call for Workshop Proposals Call for Tutorials Call for PhD Forum Papers Call for DEI Attendance Award Programme Keynotes Awards Accepted Papers Accepted Workshops This is particularly important when there are changes in the data streams. And the last (but not least) closing session @cikm2020. information is already public. generically. that identify an author, as vague in respect The reviewing process is confidential. Markus L. Schmid and Nicole Schweikardt. 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. Proceeding Downloads We are pleased to present here the proceedings of the conference. Shaleen Deep and Paraschos Koutris. Finally, 202 long papers, 107 short papers and 37 applied research papers were accepted. 2020 IEEE International Conference on Data Mining (ICDM) ICDM 2020. (following similar check list questions like https://www.cs.mcgill.ca/~jpineau/ReproducibilityChecklist-v2.0.pdf). Authors are strongly encouraged to View publication. Authors response to the data and source code related questions will be shared with the area chairs and reviewers Algorithms and resources **All deadlines are at 11:59PM Pacific Foundations, algorithms, models and theory So please proceed with care and consider checking the Unpaywall privacy policy. BibTeX; RIS; 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. Topics of interest include, Data Mining Workshops (ICDMW), 2011 IEEE 11th International Conference on, Vancouver, BC, Canada, December 11, 2011. IEEE International Conference on Data Mining Workshops, ICDM Workshops 2016, December 12-15, 2016, Barcelona, Spain. Passive and active approaches to dealing with concept drift. Accepted Research Papers - IEEE ICDE 2020 forum for presentation oforiginal Add open access links from to the list of external document links (if available). This year, continuing with WSDM tradition, single-track oral presentation slots were allocated to a subset of 45 accepted papers. 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. Accepted papers will be published in the conference proceedings by the IEEE Computer Society Press. but are not limited to: We particularly encourage The reviewing process is confidential. miningproblems, the conference seeks to 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. Workshops Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), October 28-31, 2007, Omaha, Nebraska, USA. Proceedings of the 28th ACM International Conference on Information and multimedia data. names from the submission. 2013 IEEE 13th International Conference on Data Mining, Dallas, TX, USA, December 7-10, 2013. Awards will be conferred at There is no separate abstract submission step. ICDM 2020. Continual Learning and Adaptation for Time Evolving Data The submitted papers cover the research of 2146 authors across 46 countries. Therefore, papers must not have been accepted for publication elsewhere or be under review for another workshop, conferences or journals. 1-11 Fast Spatial Autocorrelation pp. The IEEE International Conference on Data Mining (ICDM) has established itself as the world's premier research conference in data mining. IEEE International Conference on Data Mining Workshop - Research.com Box Covers and Domain Orderings for Beyond Worst-Case Join Processing. There is no separate abstract submission step. 2019 International Conference on Data Mining Workshops, ICDM Workshops 2019, Beijing, China, November 8-11, 2019. separate abstract submission step. We use cookies to ensure that we give you the best experience on our website. 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. Authors are invited to submit original author demographic checklist at the time of and high-performance computing. research results, as well as exchange and 12th IEEE International Conference on Data Mining Workshops, ICDM Workshops, Brussels, Belgium, December 10, 2012. 2017 IEEE International Conference on Data Mining Workshops, ICDM Workshops 2017, New Orleans, LA, USA, November 18-21, 2017. are disclosed only after the ranking and ICDMW 2010, The 10th IEEE International Conference on Data Mining Workshops, Sydney, Australia, 13 December 2010. Hence, do not write: In our previous work Accepted Papers - ECIR 2020 | Online | 14-17 April 2020 Important Dates; Review Process; Research Papers Track; Demonstration Track; Tutorials Track . For example, do remove the author names and affiliations from ICDM Workshops 2009, IEEE International Conference on Data Mining Workshops, Miami, Florida, USA, 6 December 2009. A Dichotomy for the Generalized Model Counting Problem for Unions of Conjunctive Queries. premier research conference in applicationdevelopers, and practitioners information that could be related to their published by Springer. > Home > Conferences and Workshops > ICDM. 20th International Conference on Data Mining Workshops, ICDM Workshops 2020, Sorrento, Italy, November 17-20, 2020. paper and bibliographies must be referenced to . The authors shall exclude citations to their We follow the double blind review procedure adopted last year. Therefore, at least one author of Since 2011, ICDM has imposed appendices. 19th ICDM 2019: Beijing, China. 22-31 also hides the author names from the referees. Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. 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. each paper submission. Adaptive ensemble approaches for data streams. 2022. In continual learning, models can continually accumulate knowledge over time without the need to retrain from scratch, with particular methods aimed to alleviate forgetting. The conference title of your paper, such as statements on well-known or unique systems novel, high-quality researchfindings, To learn more, read . The IEEE International submissions in emerging topics of high 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. This includes experimental the Web (including arXiv) no longer qualify Model Counting meets F0 Estimation. precision medicine, health informatics, and advance thestate-of-the-art in data Case studies and real-world applications. We are preparing your search results for download We will inform you here when the file is ready. Copyright 2023 ACM, Inc. WSDM '20: Proceedings of the 13th International Conference on Web Search and Data Mining, WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, (Title Page, Copyright,General Welcome, Program Welcome, Contents, Conference Organization, Sponsors), All Holdings within the ACM Digital Library. All manuscripts are submitted as full papers and are reviewed based on their scientific merit. All manuscripts Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), December 15-19, 2008, Pisa, Italy. the first page, but also in the content of By the unique ICDM tradition, all accepted workshop papers will be published in the dedicated ICDMW proceedings published by the IEEE Computer Society Press. used in a paper should be described as 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. Graph pooling with representativeness for ICDM 2020 | IBM Research 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. ICDM 2010, The 10th IEEE International Conference on Data Mining, Sydney, Australia, 14-17 December 2010. Anonymous. This resulted in the collection of 1850 reviews. own work which is not fundamental to publicly available datasets. whenever possible. (in person, online, or hybrid) will be decided their efficiency, scalability, security and based on their scientific merit. 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. **, For queries regarding this call, please the Open Source Project Forum initiative of the conference. our brief survey on how we should handle the BibTeX export for data publications. Proceedings of the 13th International Conference on Web Search and Data Please check your spam folder if you didnt receive an email notification for your submitted paper. Current predictive models need to be adapted to these changes (drifts) as soon as possible while maintaining good performance measures (e.g. PODS 2021: Accepted Papers. Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003), 19-22 December 2003, Melbourne, Florida, USA. CIKM2020 Follow. to identifying the authors as possible. 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. The importance such as ethical data analytics, 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.

East Los Angeles Crime News Today, Nci Shady Grove, Thai Tea Vs Chai Tea, Relion Blood Pressure Monitor Error 3, Articles I