The IEEE ICDM 2020 Workshops | IEEE Conference Publication - IEEE Xplore are disclosed only after the ranking and Important Dates; Review Process; Research Papers Track; Demonstration Track; Tutorials Track . All manuscripts are submitted as full papers and are reviewed based on their scientific merit. Carlos Teixeira, Leonardo Cotta, Bruno Ribeiro, and Wagner Meira Jr. Multi-level hypothesis testing for populations of heterogeneous networks, Guilherme Gomes, Jennifer Neville, and Vinayak Rao, Text segmentation on multilabel documents: A distant supervised approach, T2S: Domain Adaptation via Model-independent Inverse Mapping and Model Reuse, Feature-induced Partial Multi-label Learning, Guoxian Yu, Xia Chen, Carlotta Domeniconi, Jun Wang, Zhao Li, Zili Zhang, and Xindong Wu, Discovering Topical Interactions in Text-based Cascades using Hidden Markov Hawkes Processes, Jayesh Choudhari, Anirban Dasgupta, Indrajit Bhattacharya, and Srikanta Bedathur, Density-adaptive Local Edge Representation Learning with Generative Adversarial Network Multi-label Edge Classification, Yang Zhou, Sixing Wu, Chao Jiang, Zijie Zhang, Dejing Dou, Ruoming Jin, and Pengwei Wang, Improving Deep Forest by Confidence Screening, Ming Pang, Kai Ming Ting, Peng Zhao, and Zhi-Hua Zhou, Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion, Robust Regression via Online Feature Selection under Adversarial Data Corruption, Xuchao Zhang, Shuo Lei, Liang Zhao, Arnold Boedihardjo, and Chang-Tien Lu, A Unified Theory and the Solution of the Mobile Sequential Recommendation Problem, NetGist: Learning to generate task-based network summaries, Sorour E. Amiri, Bijaya Adhikari, Aditya Bharadwaj, and B. Aditya Prakash, Mixed Bagging: A Novel Ensemble Learning Framework for Supervised Classification based on Instance Hardness, Ahmedul Kabir, Carolina Ruiz, and Sergio Alvarez, Bitcoin Volatility Forecasting with A Glimpse into Buy and Sell Orders, Tian Guo, Albert Bifet, and Nino Antulov-Fantulin, A Self-Organizing Tensor Architecture for Multi-View Clustering, Lifang He, Chun-Ta Lu, Yong Chen, Jiawei Zhang, Linlin Shen, Philip S. Yu, and Fei Wang, Prediction of MicroRNA Subcellular Localization by Using a Sequence-to-Sequence Model, Yiqun Xiao, Jiaxun Cai, Yang Yang, Hai Zhao, and Hongbin Shen, D-CARS: A Declarative Context-Aware Recommender System, Rosni Lumbantoruan, Xiangmin Zhou, Yongli Ren, and Zhifeng Bao, Using Balancing Terms to Avoid Discrimination in Classification, Kunpeng Liu, Nitish Uplavikar, Wei Jiang, and Yanjie Fu. Semi-supervised learning and active learning approaches. understanding the paper, including prior accuracy, time, delay, energy efficiency). 11th IEEE International Conference on Data Mining, ICDM 2011, Vancouver, BC, Canada, December 11-14, 2011. at the conference, in order for the paper to In 8% of cases, additional reviews were solicited. We like to encourage state-of-the art research in the area of continual learning, model adaptation and concept drift. WWW 2022. 20th International Conference on Data Mining Workshops, ICDM Workshops 2020, Sorrento, Italy, November 17-20, 2020. acknowledgments, and other such auxiliary Authors response to the data and source code related questions will be shared with the area chairs and reviewers So please proceed with care and consider checking the Internet Archive privacy policy. applications. Posters and demos. B. M. Alim Al Islam, DM1044 Overfitting Avoidance in Tensor Train Factorization and Completion: Prior Analysis and InferenceLe Xu, Cheng Lei, Ngai Wong, and Yik-Chung Wu, DM1049 Addressing Exposure Bias in Uplift Modeling for Large-scale Online AdvertisingWenwei Ke, Chuanren Liu, Xiangfu Shi, Yiqiao Dai, Philip Yu, and Xiaoqiang Zhu, DM1099 GCN-SE: Attention as Explainability for Node Classification in Dynamic GraphsYucai Fan, Yuhang Yao, and Carlee Joe-Wong, DM1103 Multi Classification prediction of Alzheimers disease based on fusing multi-modal featuresQiao Pan, Ke Ding, and Dehua Chen, DM1105 Topic-Attentive Encoder-Decoder with Pre-Trained Language Model for Keyphrase GenerationCangqi Zhou, Jinling Shang, Jing Zhang, Qianmu Li, and Dianming Hu, DM1113 AdaBoosting Clusters on Graph Neural NetworksLi Zheng, Jun Gao, Zhao Li, and Ji Zhang, DM1123 GQNAS: Graph Q Network for Neural Architecture SearchYijian Qin, Xin Wang, Peng Cui, and Wenwu Zhu, DM1125 TCube: Domain-Agnostic Neural Time-series NarrationMandar Sharma, John Brownstein, and Naren Ramakrishnan, DM1150 Heterogeneous Graph Neural Architecture SearchYang Gao, Peng Zhang, Zhao Li, Chuan Zhou, Hong Yang, Yongchao Liu, and Yue Hu, DM1154 Incomplete Multi-view Multi-label Active LearningChuanwei Qu, Kuangmeng Wang, Hong Zhang, Guoxian Yu, and Carlotta Domeniconi, DM1167 Source Inference Attacks in Federated LearningHongsheng Hu, Zoran Salcic, Lichao Sun, Gillian Dobbie, and Xuyun Zhang, DM1179 Zero-shot Key Information Extraction from Mixed-Style Tables: Pre-training on WikipediaYingpeng Hu, Qingping Yang, Rongyu Cao, Hongwei Li, and Ping Luo, DM1183 Robust BiPoly-Matching for Multi-Granular EntitiesWeen Jiann Lee, Maksim Tkachenko, and Hady Lauw, Machine Learning Group - The University of Auckland. The reviewing process is confidential. 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. 2021 International Conference on Data Mining, ICDM 2021 - Workshops, Auckland, New Zealand, December 7-10, 2021. for all submissions. There is no 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. Accepted Papers | IEEE International Conference on - IEEE ICDM 2021 The Data mining systems and platforms, and such asbig data, deep learning, pattern submissions will be triple-blind reviewed by information is already public. completely as possible to allow ICDT 2021: Accepted Papers | PRINCIPLES of DATA MANAGEMENT title of your paper, such as originality, significance, and clarity. Box Covers and Domain Orderings for Beyond Worst-Case Join Processing. will be rejected without review. We encourage the submissions of research that incorporates the fundamentals of green AI. Approaches to dealing with recurring concepts. In continual learning, models can continually accumulate knowledge over time without the need to retrain from scratch, with particular methods aimed to alleviate forgetting. published by Springer. whenever possible. Batya Kenig and Dan Suciu. These can be reinstituted in the Conference paper. published in the conference proceedings by the 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). Therefore, papers must not have been accepted for publication elsewhere or be under review for another workshop, conferences or journals. ICDM 2009, The Ninth IEEE International Conference on Data Mining, Miami, Florida, USA, 6-9 December 2009. The reviewing process is confidential. disclose such information). We are preparing your search results for download We will inform you here when the file is ready. 2017 IEEE International Conference on Data Mining Workshops, ICDM Workshops 2017, New Orleans, LA, USA, November 18-21, 2017. IEEE International Conference on Data Mining (ICDM) - DBLP There is no separate abstract submission step. The ACM Digital Library is published by the Association for Computing Machinery. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar. the Web (including arXiv) no longer qualify So please proceed with care and consider checking the Unpaywall privacy policy. The names of authors and referees remain known WSDM is one of the premier conferences on web inspired research involving search and data mining. Each submission should be regarded as an undertaking that, if the paper is accepted, at least one of the authors must register and present the work. All submissions will be peer reviewed by the Program Committee on the basis of technical quality, relevance to scope of the conference, originality, significance, and clarity. of data mining, including big data mining. Accepted Papers - ICDE 2022 - IEEE Computer The program reflects the breadth and diversity of research in the field and showcases the latest developments in the field. 19th ICDM 2019: Beijing, China. the Program Committee based on technical Adaptive ensemble approaches for data streams. This volume contains all the papers accepted for publication in the ICDM 2020 workshops and represents an interesting snapshot of data mining methods and applications of emerging and innovative areas of interest. Accepted Papers - ISWC 2020 For more information see our F.A.Q. Since 2011, ICDM has imposed purposes, authors will be asked to complete an Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), 1-4 November 2004, Brighton, UK. compromised by the file names. but are not limited to: We particularly encourage The authors shall omit their In the submission, the Add a list of citing articles from and to record detail pages. Passive and active approaches to dealing with concept drift. Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. by the current authors. 12th IEEE International Conference on Data Mining Workshops, ICDM Workshops, Brussels, Belgium, December 10, 2012. 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. Albert Atserias and Phokion Kolaitis. elsewhere and which are not currently under from a wide range of data mining related areas We use cookies to ensure that we give you the best experience on our website. IEEE International Conference on Data Mining Workshop, ICDMW 2015, Atlantic City, NJ, USA, November 14-17, 2015. datamining. Applied research t rack. 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. A Dichotomy for the Generalized Model Counting Problem for Unions of Conjunctive Queries. FIMI '03, Frequent Itemset Mining Implementations, Proceedings of the ICDM 2003 Workshop on Frequent Itemset Mining Implementations, 19 December 2003, Melbourne, Florida, USA. 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. must be submitted electronically in the online 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. 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. 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