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ORCIDSDM 2018: San Diego, CA, USA
- Martin Ester, Dino Pedreschi:
Proceedings of the 2018 SIAM International Conference on Data Mining, SDM 2018, May 3-5, 2018, San Diego Marriott Mission Valley, San Diego, CA, USA. SIAM 2018, ISBN 978-1-61197-532-1 - Front Matter.
- Roland Glantz, Henning Meyerhenke:
Many-to-many Correspondences between Partitions: Introducing a Cut-based Approach. 1-9 - Anne Morvan, Krzysztof Choromanski, Cédric Gouy-Pailler
, Jamal Atif:
Graph sketching-based Space-efficient Data Clustering. 10-18 - Mohadeseh Ganji, Jeffrey Chan, Peter J. Stuckey, James Bailey, Christopher Leckie, Kotagiri Ramamohanarao, Ian Davidson:
Image Constrained Blockmodelling: A Constraint Programming Approach. 19-27 - Jun Wang, Cho-Jui Hsieh, Daming Shi:
NLRR++: Scalable Subspace Clustering via Non-Convex Block Coordinate Descent. 28-36 - Keqian Li, Hanwen Zha, Yu Su, Xifeng Yan:
Unsupervised Neural Categorization for Scientific Publications. 37-45 - Zilong Bai, Peter B. Walker, Ian Davidson:
Mixtures of Block Models for Brain Networks. 46-54 - Kailash Budhathoki, Jilles Vreeken:
Causal Inference on Event Sequences. 55-63 - Jiali Mao, Pengda Sun, Cheqing Jin, Aoying Zhou:
Outlier Detection over Distributed Trajectory Streams. 64-72 - Xingyu Cai, Shanglin Zhou, Sanguthevar Rajasekaran:
JUMP: A Fast Deterministic Algorithm to Find the Closest Pair of Subsequences. 73-80 - Shaden Smith, Kejun Huang, Nicholas D. Sidiropoulos, George Karypis:
Streaming Tensor Factorization for Infinite Data Sources. 81-89 - Len Feremans, Boris Cule, Bart Goethals:
Mining Top-k Quantile-based Cohesive Sequential Patterns. 90-98 - Yue Ning, Rongrong Tao, Chandan K. Reddy, Huzefa Rangwala, James C. Starz, Naren Ramakrishnan:
STAPLE: Spatio-Temporal Precursor Learning for Event Forecasting. 99-107 - Bijaya Adhikari, Pavan Rangudu, B. Aditya Prakash, Anil Vullikanti:
Near-Optimal Mapping of Network States using Probes. 108-116 - Ruihua Cheng, Zhi Wei, Kai Zhang:
Network Inference from Contrastive Groups Using Discriminative Structural Regularization. 117-125 - Sourav Medya, Arlei Silva, Ambuj K. Singh, Prithwish Basu, Ananthram Swami:
Group Centrality Maximization via Network Design. 126-134 - Rade Stanojevic, Sofiane Abbar, Saravanan Thirumuruganathan, Sanjay Chawla, Fethi Filali, Ahid Aleimat:
Robust Road Map Inference through Network Alignment of Trajectories. 135-143 - Yu Shi, Huan Gui, Qi Zhu, Lance M. Kaplan, Jiawei Han:
AspEm: Embedding Learning by Aspects in Heterogeneous Information Networks. 144-152 - Jiongqian Liang, Peter Jacobs, Jiankai Sun, Srinivasan Parthasarathy:
Semi-supervised Embedding in Attributed Networks with Outliers. 153-161 - Liuyi Yao, Lu Su, Qi Li, Yaliang Li, Fenglong Ma, Jing Gao, Aidong Zhang:
Online Truth Discovery on Time Series Data. 162-170 - Kunpeng Liu, Pengyang Wang, Jiawei Zhang, Yanjie Fu, Sajal K. Das:
Modeling the Interaction Coupling of Multi-View Spatiotemporal Contexts for Destination Prediction. 171-179 - Xian Wu, Yuxiao Dong, Baoxu Shi, Ananthram Swami, Nitesh V. Chawla:
Who will Attend This Event Together? Event Attendance Prediction via Deep LSTM Networks. 180-188 - Huandong Wang, Yong Li, Gang Wang, Depeng Jin:
You Are How You Move: Linking Multiple User Identities From Massive Mobility Traces. 189-197 - Jingtao Ding, Yanghao Li, Yong Li, Depeng Jin:
Click versus Share: A Feature-driven Study of Micro-Video Popularity and Virality in Social Media. 198-206 - Michiaki Tatsubori, Aisha Walcott-Bryant, Reginald E. Bryant, John Wamburu:
A Probabilistic Hough Transform for Opportunistic Crowd-sensing of Moving Traffic Obstacles. 207-215 - Ritchie Lee, Mykel J. Kochenderfer, Ole J. Mengshoel, Joshua Silbermann:
Interpretable Categorization of Heterogeneous Time Series Data. 216-224 - Chang Wei Tan, Matthieu Herrmann, Germain Forestier, Geoffrey I. Webb, François Petitjean:
Efficient search of the best warping window for Dynamic Time Warping. 225-233 - Yilin Shen, Yanping Chen, Eamonn J. Keogh, Hongxia Jin:
Accelerating Time Series Searching with Large Uniform Scaling. 234-242 - Xiaosheng Li, Jessica Lin:
Evolving Separating References for Time Series Classification. 243-251 - Guruprasad Nayak, Varun Mithal, Xiaowei Jia, Vipin Kumar:
Classifying Multivariate Time Series by Learning Sequence-level Discriminative Patterns. 252-260 - Tengfei Ma, Cao Xiao, Fei Wang:
Health-ATM: A Deep Architecture for Multifaceted Patient Health Record Representation and Risk Prediction. 261-269 - Mengdi Huai, Chenglin Miao, Qiuling Suo, Yaliang Li, Jing Gao, Aidong Zhang:
Uncorrelated Patient Similarity Learning. 270-278 - Weitong Chen, Sen Wang, Xiang Zhang, Lina Yao, Lin Yue, Buyue Qian, Xue Li:
EEG-based Motion Intention Recognition via Multi-task RNNs. 279-287 - Yan Li, Tao Yang, Jiayu Zhou, Jieping Ye:
Multi-Task Learning based Survival Analysis for Predicting Alzheimer's Disease Progression with Multi-Source Block-wise Missing Data. 288-296 - Djordje Gligorijevic, Jelena Stojanovic, Wayne Satz, Ivan Stojkovic, Kraftin Schreyer, Daniel Del Portal, Zoran Obradovic:
Deep Attention Model for Triage of Emergency Department Patients. 297-305 - Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Q. Phung:
Learning Graph Representation via Frequent Subgraphs. 306-314 - Muhao Chen, Yingtao Tian, Xuelu Chen, Zijun Xue, Carlo Zaniolo:
On2Vec: Embedding-based Relation Prediction for Ontology Population. 315-323 - Fei Jiang, Lifang He, Yi Zheng, Enqiang Zhu, Jin Xu, Philip S. Yu:
On Spectral Graph Embedding: A Non-Backtracking Perspective and Graph Approximation. 324-332 - José Bento, Stratis Ioannidis:
A Family of Tractable Graph Distances. 333-341 - Yujun Yan, Mark Heimann, Di Jin, Danai Koutra:
Fast Flow-based Random Walk with Restart in a Multi-query Setting. 342-350 - Pengyang Wang, Jiawei Zhang, Guannan Liu, Yanjie Fu, Charu C. Aggarwal:
Ensemble-Spotting: Ranking Urban Vibrancy via POI Embedding with Multi-view Spatial Graphs. 351-359 - Sanjar Karaev, James L. Hook, Pauli Miettinen:
Latitude: A Model for Mixed Linear-Tropical Matrix Factorization. 360-368 - Johannes Schneider, Michail Vlachos:
Topic Modeling based on Keywords and Context. 369-377 - Roy Ka-Wei Lee, Tuan-Anh Hoang, Ee-Peng Lim:
Discovering Hidden Topical Hubs and Authorities in Online Social Networks. 378-386 - Ekta Gujral, Ravdeep Pasricha, Evangelos E. Papalexakis:
SamBaTen: Sampling-based Batch Incremental Tensor Decomposition. 387-395 - Bo Yang, Ahmed S. Zamzam, Nicholas D. Sidiropoulos:
ParaSketch: Parallel Tensor Factorization via Sketching. 396-404 - Sibylle Hess, Nico Piatkowski, Katharina Morik:
The Trustworthy Pal: Controlling the False Discovery Rate in Boolean Matrix Factorization. 405-413 - Trefor W. Evans, Prasanth B. Nair:
Exploiting Structure for Fast Kernel Learning. 414-422 - Yaxin Peng, Lingfang Hu, Shihui Ying, Chaomin Shen:
Global Nonlinear Metric Learning by Gluing Local Linear Metrics. 423-431 - Shalmali Joshi, Rajiv Khanna, Joydeep Ghosh:
Co-regularized Monotone Retargeting for Semi-supervised LeTOR. 432-440 - Harshal A. Chaudhari, Michael Mathioudakis, Evimaria Terzi:
Markov Chain Monitoring. 441-449 - Qiaoyu Tan, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Zili Zhang:
Multi-view Weak-label Learning based on Matrix Completion. 450-458 - Nayyar Abbas Zaidi, François Petitjean, Geoffrey I. Webb:
Efficient and Effective Accelerated Hierarchical Higher-Order Logistic Regression for Large Data Quantities. 459-467 - Shin Ando:
Discriminative Prototype Set Learning for Nearest Neighbor Classification. 468-476 - Zhiyun Ren, Xia Ning, Huzefa Rangwala:
ALE: Additive Latent Effect Models for Grade Prediction. 477-485 - Chien-Wen Huang, Chung-Kuang Chou, Ming-Syan Chen:
A Salient Ensemble of Trees using Cascaded Linear Classifiers with Feature-Cost Constraints. 486-494 - Marawan Shalaby, Jan Stutzki, Matthias Schubert, Stephan Günnemann:
An LSTM Approach to Patent Classification based on Fixed Hierarchy Vectors. 495-503 - Wei-Lin Chiang, Yu-Sheng Li, Ching-Pei Lee, Chih-Jen Lin:
Limited-memory Common-directions Method for Distributed Ll-regularized Linear Classification. 504-512 - Tushar Semwal, Promod Yenigalla, Gaurav Mathur, Shivashankar B. Nair:
A Practitioners' Guide to Transfer Learning for Text Classification using Convolutional Neural Networks. 513-521 - Sunav Choudhary, Gaurush Hiranandani, Shiv Kumar Saini:
Sparse Decomposition for Time Series Forecasting and Anomaly Detection. 522-530 - Bryan Hooi, Hyun Ah Song, Amritanshu Pandey, Marko Jereminov, Larry T. Pileggi, Christos Faloutsos:
StreamCast: Fast and Online Mining of Power Grid Time Sequences. 531-539 - Markus Brill, Till Fluschnik, Vincent Froese, Brijnesh J. Jain, Rolf Niedermeier, David Schultz:
Exact Mean Computation in Dynamic Time Warping Spaces. 540-548 - Chainarong Amornbunchornvej, Tanya Y. Berger-Wolf:
Framework for Inferring Leadership Dynamics of Complex Movement from Time Series. 549-557 - Chenglong Dai, Jia Wu, Dechang Pi, Lin Cui:
Brain EEG Time Series Selection: A Novel Graph-Based Approach for Classification. 558-566 - Keiichi Kisamori, Takashi Washio, Yoshio Kameda, Ryohei Fujimaki:
A Rare and Critical Condition Search Technique and its Application to Telescope Stray Light Analysis. 567-575 - Ya-Wen Teng, Chih-Hua Tai, Philip S. Yu, Ming-Syan Chen:
Revenue Maximization on the Multi-grade Product. 576-584 - Emre Eftelioglu, Xun Tang, Shashi Shekhar:
Avoidance Region Discovery: A Summary of Results. 585-593 - Zhengyang Wang, Shuiwang Ji:
Learning Convolutional Text Representations for Visual Question Answering. 594-602 - Ximing Li, Changchun Li, Jinjin Chi, Jihong Ouyang, Wenting Wang:
Black-box Expectation Propagation for Bayesian Models. 603-611 - Konstantina Christakopoulou, Arindam Banerjee:
Learning to Interact with Users: A Collaborative-Bandit Approach. 612-620 - Peng Yang, Peilin Zhao, Yong Liu, Xin Gao:
Robust Cost-Sensitive Learning for Recommendation with Implicit Feedback. 621-629 - Min Yang, Qiang Qu, Kai Lei, Jia Zhu, Zhou Zhao, Xiaojun Chen, Joshua Zhexue Huang:
Investigating Deep Reinforcement Learning Techniques in Personalized Dialogue Generation. 630-638 - Fei Tan, Kuang Du, Zhi Wei, Haoran Liu, Chenguang Qin, Ran Zhu:
Modeling Item-specific Effects for Video Click. 639-647 - Mengting Wan, Julian J. McAuley:
One-Class Recommendation with Asymmetric Textual Feedback. 648-656 - Qing Wang, Tao Li, S. S. Iyengar, Larisa Shwartz, Genady Ya. Grabarnik:
Online IT Ticket Automation Recommendation Using Hierarchical Multi-armed Bandit Algorithms. 657-665 - Han Xiao, Polina Rozenshtein, Nikolaj Tatti, Aristides Gionis:
Reconstructing a cascade from temporal observations. 666-674 - Wenchao Yu, Charu C. Aggarwal, Wei Wang:
Modeling Co-Evolution Across Multiple Networks. 675-683 - Jundong Li, Chen Chen, Hanghang Tong, Huan Liu:
Multi-Layered Network Embedding. 684-692 - Tianyuan Jin, Tong Xu, Hui Zhong, Enhong Chen, Zhefeng Wang, Qi Liu:
Maximizing the Effect of Information Adoption: A General Framework. 693-701 - Ekta Gujral, Evangelos E. Papalexakis:
SMACD: Semi-supervised Multi-Aspect Community Detection. 702-710 - Liang Wu, Jundong Li, Fred Morstatter, Huan Liu:
Toward Relational Learning with Misinformation. 711-719 - Li-Yen Kuo, Chung-Kuang Chou, Ming-Syan Chen:
Personalized Ranking on Poisson Factorization. 720-728 - Ruocheng Guo, Hamidreza Alvari, Paulo Shakarian:
Strongly Hierarchical Factorization Machines and ANOVA Kernel Regression. 729-737 - Pablo Nascimento da Silva, Alexandre Plastino, Alex Alves Freitas:
A Novel Genetic Algorithm for Feature Selection in Hierarchical Feature Spaces. 738-746 - Richard Leibrandt, Stephan Günnemann:
Making Kernel Density Estimation Robust towards Missing Values in Highly Incomplete Multivariate Data without Imputation. 747-755 - Arnaud Giacometti, Arnaud Soulet:
Dense Neighborhood Pattern Sampling in Numerical Data. 756-764
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