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19th ICDM 2019: Beijing, China
- Jianyong Wang, Kyuseok Shim, Xindong Wu:
2019 IEEE International Conference on Data Mining, ICDM 2019, Beijing, China, November 8-11, 2019. IEEE 2019, ISBN 978-1-7281-4604-1
Regular Papers
- Uchenna Akujuobi, Yufei Han, Qiannan Zhang, Xiangliang Zhang:
Collaborative Graph Walk for Semi-Supervised Multi-label Node Classification. 1-10 - Basmah Altaf, Uchenna Akujuobi, Lu Yu, Xiangliang Zhang:
Dataset Recommendation via Variational Graph Autoencoder. 11-20 - Sourabh Balgi, Ambedkar Dukkipati:
CUDA: Contradistinguisher for Unsupervised Domain Adaptation. 21-30 - Lei Cai, Shuiwang Ji:
An Efficient Policy Gradient Method for Conditional Dialogue Generation. 31-40 - Zixin Cai, Xinyue Wang, Mingjie Zhou, Jian Xu, Liping Jing:
Supervised Class Distribution Learning for GANs-Based Imbalanced Classification. 41-50 - Jinxin Chang, Ruifang He, Haiyang Xu, Kun Han, Longbiao Wang, Xiangang Li, Jianwu Dang:
NVSRN: A Neural Variational Scaling Reasoning Network for Initiative Response Generation. 51-60 - Haipeng Chen, Yan Jiao, Zhiwei (Tony) Qin, Xiaocheng Tang, Hao Li, Bo An, Hongtu Zhu, Jieping Ye:
InBEDE: Integrating Contextual Bandit with TD Learning for Joint Pricing and Dispatch of Ride-Hailing Platforms. 61-70 - Xiangning Chen, Bo Qiao, Weiyi Zhang, Wei Wu, Murali Chintalapati, Dongmei Zhang, Qingwei Lin, Chuan Luo, Xudong Li, Hongyu Zhang, Yong Xu, Yingnong Dang, Kaixin Sui, Xu Zhang:
Neural Feature Search: A Neural Architecture for Automated Feature Engineering. 71-80 - Qing Chen, Jianji Wang, Xuguang Lan, Nanning Zheng:
Preference Relationship-Based CrossCMN Scheme for Answer Ranking in Community QA. 81-90 - Pantelis Chronis, Spiros Athanasiou, Spiros Skiadopoulos:
Automatic Clustering by Detecting Significant Density Dips in Multiple Dimensions. 91-100 - Wangzhi Dai, Kenney Ng, Kristen A. Severson, Wei Huang, Fred Anderson, Collin M. Stultz:
Generative Oversampling with a Contrastive Variational Autoencoder. 101-109 - Monidipa Das, Mahardhika Pratama, Septiviana Savitri, Jie Zhang:
MUSE-RNN: A Multilayer Self-Evolving Recurrent Neural Network for Data Stream Classification. 110-119 - Edouard Delasalles, Sylvain Lamprier, Ludovic Denoyer:
Learning Dynamic Author Representations with Temporal Language Models. 120-129 - Sunipa Dev, Safia Hassan, Jeff M. Phillips:
Closed Form Word Embedding Alignment. 130-139 - Pengfei Ding, Guanfeng Liu, Pengpeng Zhao, An Liu, Zhixu Li, Kai Zheng:
Reinforcement Learning Based Monte Carlo Tree Search for Temporal Path Discovery. 140-149 - Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu:
Learning Credible Deep Neural Networks with Rationale Regularization. 150-159 - Jiadi Du, Yunchao Zhang, Pengyang Wang, Jennifer L. Leopold, Yanjie Fu:
Beyond Geo-First Law: Learning Spatial Representations via Integrated Autocorrelations and Complementarity. 160-169 - Liang Duan, Charu C. Aggarwal, Shuai Ma, Saket Sathe:
Improving Spectral Clustering with Deep Embedding and Cluster Estimation. 170-179 - Subhabrata Dutta, Dipankar Das, Tanmoy Chakraborty:
Modeling Engagement Dynamics of Online Discussions using Relativistic Gravitational Theory. 180-189 - Zhen Fang, Yang Li, Chuanren Liu, Wenxiang Zhu, Yu Zheng, Wenjun Zhou:
Large-Scale Personalized Delivery for Guaranteed Display Advertising with Real-Time Pacing. 190-199 - Yujuan Feng, Zhenxing Xu, Lin Gan, Ning Chen, Bin Yu, Ting Chen, Fei Wang:
DCMN: Double Core Memory Network for Patient Outcome Prediction with Multimodal Data. 200-209 - Oluwaseyi Feyisetan, Tom Diethe, Thomas Drake:
Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text. 210-219 - Yifeng Gao, Jessica Lin:
Discovering Subdimensional Motifs of Different Lengths in Large-Scale Multivariate Time Series. 220-229 - Majid Ghasemi-Gol, Jay Pujara, Pedro A. Szekely:
Tabular Cell Classification Using Pre-Trained Cell Embeddings. 230-239 - Heitor Murilo Gomes, Jesse Read, Albert Bifet:
Streaming Random Patches for Evolving Data Stream Classification. 240-249 - Xiaojie Guo, Liang Zhao, Cameron Nowzari, Setareh Rafatirad, Houman Homayoun, Sai Manoj Pudukotai Dinakarrao:
Deep Multi-attributed Graph Translation with Node-Edge Co-Evolution. 250-259 - Karthik S. Gurumoorthy, Amit Dhurandhar, Guillermo A. Cecchi, Charu C. Aggarwal:
Efficient Data Representation by Selecting Prototypes with Importance Weights. 260-269 - Shah Muhammad Hamdi, Rafal A. Angryk:
Interpretable Feature Learning of Graphs using Tensor Decomposition. 270-279 - Shuo He, Ke Deng, Li Li, Senlin Shu, Li Liu:
Discriminatively Relabel for Partial Multi-label Learning. 280-288 - Mark Heimann, Tara Safavi, Danai Koutra:
Distribution of Node Embeddings as Multiresolution Features for Graphs. 289-298 - Takato Honda, Yasuko Matsubara, Ryo Neyama, Mutsumi Abe, Yasushi Sakurai:
Multi-aspect Mining of Complex Sensor Sequences. 299-308 - Chen Huang, Peiyan Li, Chongming Gao, Qinli Yang, Junming Shao:
Online Budgeted Least Squares with Unlabeled Data. 309-318 - Hao Huang, Chenxiao Xu, Shinjae Yoo:
Bi-directional Causal Graph Learning through Weight-Sharing and Low-Rank Neural Network. 319-328 - Shima Imani, Eamonn J. Keogh:
Matrix Profile XIX: Time Series Semantic Motifs: A New Primitive for Finding Higher-Level Structure in Time Series. 329-338 - Yujia Jin, Qi Bao, Zhongzhi Zhang:
Forest Distance Closeness Centrality in Disconnected Graphs. 339-348 - Nils M. Kriege, Pierre-Louis Giscard, Franka Bause, Richard C. Wilson:
Computing Optimal Assignments in Linear Time for Approximate Graph Matching. 349-358 - Yunshi Lan, Shuohang Wang, Jing Jiang:
Multi-hop Knowledge Base Question Answering with an Iterative Sequence Matching Model. 359-368 - Jae-woong Lee, Minjin Choi, Jongwuk Lee, Hyunjung Shim:
Collaborative Distillation for Top-N Recommendation. 369-378 - Keqian Li, Shiyang Li, Semih Yavuz, Hanwen Zha, Yu Su, Xifeng Yan:
HierCon: Hierarchical Organization of Technical Documents Based on Concepts. 379-388 - Xiaoyu Li, Buyue Qian, Jishang Wei, An Li, Xuan Liu, Qinghua Zheng:
Classify EEG and Reveal Latent Graph Structure with Spatio-Temporal Graph Convolutional Neural Network. 389-398 - Tianyu Li, Chien-Chih Wang, Yukun Ma, Patricia Ortal, Qifang Zhao, Björn Stenger, Yu Hirate:
Learning Classifiers on Positive and Unlabeled Data with Policy Gradient. 399-408 - Zhuliu Li, Wei Zhang, Rong Stephanie Huang, Rui Kuang:
Learning a Low-Rank Tensor of Pharmacogenomic Multi-relations from Biomedical Networks. 409-418 - Adi Lin, Jie Lu, Junyu Xuan, Fujin Zhu, Guangquan Zhang:
One-Stage Deep Instrumental Variable Method for Causal Inference from Observational Data. 419-428 - Xixun Lin, Hong Yang, Jia Wu, Chuan Zhou, Bin Wang:
Guiding Cross-lingual Entity Alignment via Adversarial Knowledge Embedding. 429-438 - Fenglin Liu, Meng Gao, Tianhao Zhang, Yuexian Zou:
Exploring Semantic Relationships for Image Captioning without Parallel Data. 439-448 - Xuanwu Liu, Zhao Li, Jun Wang, Guoxian Yu, Carlotta Domeniconi, Xiangliang Zhang:
Cross-Modal Zero-Shot Hashing. 449-458 - Kin Sum Liu, Chaowei Xiao, Bo Li, Jie Gao:
Performing Co-membership Attacks Against Deep Generative Models. 459-467 - Kachun Lo, Tsukasa Ishigaki:
Matching Novelty While Training: Novel Recommendation Based on Personalized Pairwise Loss Weighting. 468-477 - Xuewei Ma, Geng Qin, Zhiyang Qiu, Mingxin Zheng, Zhe Wang:
RiWalk: Fast Structural Node Embedding via Role Identification. 478-487 - Atsushi Nitanda, Tomoya Murata, Taiji Suzuki:
Sharp Characterization of Optimal Minibatch Size for Stochastic Finite Sum Convex Optimization. 488-497 - Xueping Peng, Guodong Long, Tao Shen, Sen Wang, Jing Jiang, Michael Blumenstein:
Temporal Self-Attention Network for Medical Concept Embedding. 498-507 - Rameshwar Pratap, Debajyoti Bera, Karthik Revanuru:
Efficient Sketching Algorithm for Sparse Binary Data. 508-517 - Peng Qi, Juan Cao, Tianyun Yang, Junbo Guo, Jintao Li:
Exploiting Multi-domain Visual Information for Fake News Detection. 518-527 - Tara Safavi, Caleb Belth, Lukas Faber, Davide Mottin, Emmanuel Müller, Danai Koutra:
Personalized Knowledge Graph Summarization: From the Cloud to Your Pocket. 528-537 - Jingyu Shao, Qing Wang, Fangbing Liu:
Learning to Sample: An Active Learning Framework. 538-547 - Fangzhou Shi, Shan You, Chang Xu:
Reinforced Molecule Generation with Heterogeneous States. 548-557 - Satyaki Sikdar, Justus Hibshman, Tim Weninger:
Modeling Graphs with Vertex Replacement Grammars. 558-567 - Wei Tu, Peng Liu, Jingyu Zhao, Yi Liu, Linglong Kong, Guodong Li, Bei Jiang, Guangjian Tian, Hengshuai Yao:
M-estimation in Low-Rank Matrix Factorization: A General Framework. 568-577 - Ruosi Wan, Haoyi Xiong, Xingjian Li, Zhanxing Zhu, Jun Huan:
Towards Making Deep Transfer Learning Never Hurt. 578-587 - Lichen Wang, Zhengming Ding, Seungju Han, Jae-Joon Han, Changkyu Choi, Yun Fu:
Generative Correlation Discovery Network for Multi-label Learning. 588-597 - Daixin Wang, Yuan Qi, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang:
A Semi-Supervised Graph Attentive Network for Financial Fraud Detection. 598-607 - Huizhao Wang, Guanfeng Liu, Yan Zhao, Bolong Zheng, Pengpeng Zhao, Kai Zheng:
DMFP: A Dynamic Multi-faceted Fine-Grained Preference Model for Recommendation. 608-617 - Qi Wang, Weiliang Zhao, Jian Yang, Jia Wu, Wenbin Hu, Qianli Xing:
DeepTrust: A Deep User Model of Homophily Effect for Trust Prediction. 618-627 - Yanyan Wei, Zhao Zhang, Haijun Zhang, Richang Hong, Meng Wang:
A Coarse-to-Fine Multi-stream Hybrid Deraining Network for Single Image Deraining. 628-637 - Jörg Wicker, Yan Cathy Hua, Rayner Rebello, Bernhard Pfahringer:
XOR-Based Boolean Matrix Decomposition. 638-647 - Man Wu, Shirui Pan, Xingquan Zhu, Chuan Zhou, Lei Pan:
Domain-Adversarial Graph Neural Networks for Text Classification. 648-657 - Qianqian Xie, Jimin Huang, Min Peng, Yihan Zhang, Kaifei Peng, Hua Wang:
Discriminative Regularized Deep Generative Models for Semi-Supervised Learning. 658-667 - Zuobin Xiong, Wei Li, Qilong Han, Zhipeng Cai:
Privacy-Preserving Auto-Driving: A GAN-Based Approach to Protect Vehicular Camera Data. 668-677 - Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu, Bo Du, Jian Yang:
Social Trust Network Embedding. 678-687 - Xi Yang, Yuyao Yan, Kaizhu Huang, Rui Zhang:
VSB-DVM: An End-to-End Bayesian Nonparametric Generalization of Deep Variational Mixture Model. 688-697 - Carl Yang, Jieyu Zhang, Jiawei Han:
Neural Embedding Propagation on Heterogeneous Networks. 698-707 - Fanghua Ye, Chuan Chen, Zibin Zheng, Rong-Hua Li, Jeffrey Xu Yu:
Discrete Overlapping Community Detection with Pseudo Supervision. 708-717 - Yuyang Ye, Hengshu Zhu, Tong Xu, Fuzhen Zhuang, Runlong Yu, Hui Xiong:
Identifying High Potential Talent: A Neural Network Based Dynamic Social Profiling Approach. 718-727 - Changchang Yin, Buyue Qian, Jishang Wei, Xiaoyu Li, Xianli Zhang, Yang Li, Qinghua Zheng:
Automatic Generation of Medical Imaging Diagnostic Report with Hierarchical Recurrent Neural Network. 728-737 - Changchang Yin, Rongjian Zhao, Buyue Qian, Xin Lv, Ping Zhang:
Domain Knowledge Guided Deep Learning with Electronic Health Records. 738-747 - Yang You, Yuxiong He, Samyam Rajbhandari, Wenhan Wang, Cho-Jui Hsieh, Kurt Keutzer, James Demmel:
Fast LSTM Inference by Dynamic Decomposition on Cloud Systems. 748-757 - Wenchao Yu, Wei Cheng, Charu C. Aggarwal, Bo Zong, Haifeng Chen, Wei Wang:
Self-Attentive Attributed Network Embedding Through Adversarial Learning. 758-767 - Junliang Yu, Min Gao, Hongzhi Yin, Jundong Li, Chongming Gao, Qinyong Wang:
Generating Reliable Friends via Adversarial Training to Improve Social Recommendation. 768-777 - Chaohui Yu, Jindong Wang, Yiqiang Chen, Meiyu Huang:
Transfer Learning with Dynamic Adversarial Adaptation Network. 778-786 - Lingyun Yu, Jun Yu, Qiang Ling:
Mining Audio, Text and Visual Information for Talking Face Generation. 787-795 - Chunyuan Yuan, Qianwen Ma, Wei Zhou, Jizhong Han, Songlin Hu:
Jointly Embedding the Local and Global Relations of Heterogeneous Graph for Rumor Detection. 796-805 - Hao Yuan, Na Zou, Shaoting Zhang, Hanchuan Peng, Shuiwang Ji:
Learning Hierarchical and Shared Features for Improving 3D Neuron Reconstruction. 806-815 - Lin Zhang, Alexander Gorovits, Petko Bogdanov:
PERCeIDs: PERiodic CommunIty Detection. 816-825 - Shufei Zhang, Kaizhu Huang, Rui Zhang, Amir Hussain:
Generalized Adversarial Training in Riemannian Space. 826-835 - Zhao Zhang, Yulin Sun, Zheng Zhang, Yang Wang, Guangcan Liu, Meng Wang:
Learning Structured Twin-Incoherent Twin-Projective Latent Dictionary Pairs for Classification. 836-845 - Zhao Zhang, Lei Wang, Sheng Li, Yang Wang, Zheng Zhang, Zhengjun Zha, Meng Wang:
Adaptive Structure-Constrained Robust Latent Low-Rank Coding for Image Recovery. 846-855 - Chen Zhang, Hao Wang, Liang Zhou, Yijun Wang, Can Chen:
Machine Comprehension-Incorporated Relevance Matching. 856-865 - Xitong Zhang, Liyang Xie, Zheng Wang, Jiayu Zhou:
Boosted Trajectory Calibration for Traffic State Estimation. 866-875 - Yu Zhang, Frank F. Xu, Sha Li, Yu Meng, Xuan Wang, Qi Li, Jiawei Han:
HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories. 876-885 - Qi Zhang, Tong Xu, Hengshu Zhu, Lifu Zhang, Hui Xiong, Enhong Chen, Qi Liu:
Aftershock Detection with Multi-scale Description Based Neural Network. 886-895 - Xiang Zhang, Lina Yao, Xianzhi Wang, Wenjie Zhang, Shuai Zhang, Yunhao Liu:
Know Your Mind: Adaptive Cognitive Activity Recognition with Reinforced CNN. 896-905 - Lihao Zhang, Zeyang Ye, Keli Xiao, Bo Jin:
A Parallel Simulated Annealing Enhancement of the Optimal-Matching Heuristic for Ridesharing. 906-915 - Chen Zhao, Feng Chen:
Rank-Based Multi-task Learning for Fair Regression. 916-925 - Kai Zhou, Tomasz P. Michalak, Yevgeniy Vorobeychik:
Adversarial Robustness of Similarity-Based Link Prediction. 926-935 - Zachary Zimmerman, Nader Shakibay Senobari, Gareth J. Funning, Evangelos E. Papalexakis, Samet Oymak, Philip Brisk, Eamonn J. Keogh:
Matrix Profile XVIII: Time Series Mining in the Face of Fast Moving Streams using a Learned Approximate Matrix Profile. 936-945
Short Papers
- Nazmiye Ceren Abay, Cuneyt Gurcan Akcora, Yulia R. Gel, Murat Kantarcioglu, Umar D. Islambekov, Yahui Tian, Bhavani Thuraisingham:
ChainNet: Learning on Blockchain Graphs with Topological Features. 946-951 - Roy Assaf, Ioana Giurgiu, Frank Bagehorn, Anika Schumann:
MTEX-CNN: Multivariate Time Series EXplanations for Predictions with Convolutional Neural Networks. 952-957 - Runxue Bao, Bin Gu, Heng Huang:
Efficient Approximate Solution Path Algorithm for Order Weight L_1-Norm with Accuracy Guarantee. 958-963 - Christian Bock, Matteo Togninalli, M. Elisabetta Ghisu, Thomas Gumbsch, Bastian Rieck, Karsten M. Borgwardt:
A Wasserstein Subsequence Kernel for Time Series. 964-969 - Xin-Qiang Cai, Peng Zhao, Kai-Ming Ting, Xin Mu, Yuan Jiang:
Nearest Neighbor Ensembles: An Effective Method for Difficult Problems in Streaming Classification with Emerging New Classes. 970-975 - Haipeng Chen, Jing Liu, Rui Liu, Noseong Park, V. S. Subrahmanian:
VASE: A Twitter-Based Vulnerability Analysis and Score Engine. 976-981 - Chao Chen, Yifei Liu, Xi Zhang, Sihong Xie:
Scalable Explanation of Inferences on Large Graphs. 982-987 - Yujun Chen, Yuanhong Wang, Yutao Zhang, Juhua Pu, Xiangliang Zhang:
AMENDER: An Attentive and Aggregate Multi-layered Network for Dataset Recommendation. 988-993 - Tianwen Chen, Raymond Chi-Wing Wong:
Session-Based Recommendation with Local Invariance. 994-999 - Mingyue Cheng, Runlong Yu, Qi Liu, Vincent W. Zheng, Hongke Zhao, Hefu Zhang, Enhong Chen:
Alpha-Beta Sampling for Pairwise Ranking in One-Class Collaborative Filtering. 1000-1005 - Seungtaek Choi, Haeju Park, Seung-won Hwang:
Counterfactual Attention Supervision. 1006-1011 - Yunfei Chu, Caili Guo, Tongze He, Yaqing Wang, Jenq-Neng Hwang, Chunyan Feng:
Inductive Embedding Learning on Attributed Heterogeneous Networks via Multi-task Sequence-to-Sequence Learning. 1012-1017 - Luciano Di Palma, Yanlei Diao, Anna Liu:
A Factorized Version Space Algorithm for "Human-In-the-Loop" Data Exploration. 1018-1023 - Daniel J. DiTursi, Carolyn S. Kaminski, Petko Bogdanov:
Optimal Timelines for Network Processes. 1024-1029 - Dhivya Eswaran, Christos Faloutsos, Nina Mishra, Yonatan Naamad:
Intervention-Aware Early Warning. 1030-1035 - Jingyue Gao, Xiting Wang, Yasha Wang, Zhao Yang, Junyi Gao, Jiangtao Wang, Wen Tang, Xing Xie:
CAMP: Co-Attention Memory Networks for Diagnosis Prediction in Healthcare. 1036-1041 - Yuyang Gao, Lingfei Wu, Houman Homayoun, Liang Zhao:
DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums. 1042-1047 - Rong Gao, Haifeng Xia, Jing Li, Donghua Liu, Shuai Chen, Gang Chun:
DRCGR: Deep Reinforcement Learning Framework Incorporating CNN and GAN-Based for Interactive Recommendation. 1048-1053 - Chuancai Ge, Yang Wang, Xike Xie, Hengchang Liu, Zhengyang Zhou:
An Integrated Model for Urban Subregion House Price Forecasting: A Multi-source Data Perspective. 1054-1059 - Vincent Grari, Boris Ruf, Sylvain Lamprier, Marcin Detyniecki:
Fair Adversarial Gradient Tree Boosting. 1060-1065