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ORCIDSDM 2017: Houston, Texas, USA
- Nitesh V. Chawla, Wei Wang:
Proceedings of the 2017 SIAM International Conference on Data Mining, Houston, Texas, USA, April 27-29, 2017. SIAM 2017, ISBN 978-1-61197-497-3 - Front Matter. 1-10
- Suhang Wang
, Charu C. Aggarwal, Huan Liu:
Using a Random Forest to Inspire a Neural Network and Improving on It. 1-9 - Zhi Nie, Binbin Lin, Shuai Huang, Naren Ramakrishnan, Wei Fan, Jieping Ye:
Pruning Decision Trees via Max-Heap Projection. 10-18 - Yi Ding, Sheng-Jun Huang, Chen Zu, Daoqiang Zhang:
Margin Distribution Logistic Machine. 19-27 - Yanbing Xue, Milos Hauskrecht:
Active Learning of Classification Models with Likert-Scale Feedback. 28-35 - Ryan McBride, Ke Wang, Viswanadh Nekkanti, Wenyuan Li:
Risk Clearance with Guaranteed Precision. 36-44 - Yashu Liu, Shuang Qiu, Ping Zhang, Pinghua Gong, Fei Wang, Guoliang Xue, Jieping Ye:
Computational Drug Discovery with Dyadic Positive-Unlabeled Learning. 45-53 - Muhammad Yousefnezhad, Daoqiang Zhang:
Multi-Region Neural Representation: A novel model for decoding visual stimuli in human brains. 54-62 - Qiong Hu, Tomasz Imielinski:
ALPINE: Progressive Itemset Mining with Definite Guarantees. 63-71 - Ioakeim Perros, Fei Wang, Ping Zhang, Peter B. Walker, Richard W. Vuduc, Jyotishman Pathak, Jimeng Sun:
Polyadic Regression and its Application to Chemogenomics. 72-80 - Honglei Liu, Bian Wu:
Active Learning of Functional Networks from Spike Trains. 81-89 - Jinghui Chen, Saket Sathe, Charu C. Aggarwal, Deepak S. Turaga:
Outlier Detection with Autoencoder Ensembles. 90-98 - Liang Wu, Jundong Li, Xia Hu, Huan Liu:
Gleaning Wisdom from the Past: Early Detection of Emerging Rumors in Social Media. 99-107 - Daniel Y. T. Chino, Alceu Ferraz Costa, Agma J. M. Traina, Christos Faloutsos:
VolTime: Unsupervised Anomaly Detection on Users' Online Activity Volume. 108-116 - Houping Xiao, Jing Gao, Long H. Vu, Deepak S. Turaga:
Detecting Malicious Behavior in Computer Networks via Cost-Sensitive and Connectivity Constrained Classification. 117-125 - Roel Bertens, Jilles Vreeken, Arno Siebes:
Efficiently Discovering Unexpected Pattern-Co-Occurrences. 126-134 - Heidar Davoudi, Morteza Zihayat, Aijun An:
Time-Aware Subscription Prediction Model for User Acquisition in Digital News Media. 135-143 - Dhivya Eswaran, Stephan Günnemann, Christos Faloutsos:
The Power of Certainty: A Dirichlet-Multinomial Model for Belief Propagation. 144-152 - Yexun Zhang, Yanfeng Wang, Wenbin Cai, Siyuan Zhou, Ya Zhang:
From Theory to Practice: Efficient Active Cost-sensitive Classification with Expected Error Reduction. 153-161 - Michael T. Lash, Qihang Lin, W. Nick Street, Jennifer G. Robinson, Jeffrey W. Ohlmann:
Generalized Inverse Classification. 162-170 - Xiaowei Jia, Ankush Khandelwal, Guruprasad Nayak, James Gerber, Kimberly Carlson, Paul C. West, Vipin Kumar:
Predict Land Covers with Transition Modeling and Incremental Learning. 171-179 - Xinyue Liu, Xiangnan Kong, Ann B. Ragin:
Unified and Contrasting Graphical Lasso for Brain Network Discovery. 180-188 - Bokai Cao, Lifang He, Xiaokai Wei, Mengqi Xing, Philip S. Yu, Heide Klumpp, Alex D. Leow:
t-BNE: Tensor-based Brain Network Embedding. 189-197 - Chao Che, Cao Xiao, Jian Liang, Bo Jin, Jiayu Zho, Fei Wang:
An RNN Architecture with Dynamic Temporal Matching for Personalized Predictions of Parkinson's Disease. 198-206 - Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, Jennifer G. Dy:
Clustering with Domain-Specific Usefulness Scores. 207-215 - Xiao Fu, Kejun Huang, Otilia Stretcu, Hyun Ah Song, Evangelos E. Papalexakis, Partha P. Talukdar, Tom M. Mitchell, Nicholas D. Sidiropoulos, Christos Faloutsos, Barnabás Póczos:
BrainZoom: High Resolution Reconstruction from Multi-modal Brain Signals. 216-227 - Amit Dhurandhar, Margareta Ackerman, Xiang Wang:
Uncovering Group Level Insights with Accordant Clustering. 228-236 - Anni Coden, Marina Danilevsky, Daniel Gruhl, Linda Kato, Meena Nagarajan:
A Method to Accelerate Human in the Loop Clustering. 237-245 - Aghiles Salah, Mohamed Nadif:
Model-based von Mises-Fisher Co-clustering with a Conscience. 246-254 - Natali Ruchansky, Mark Crovella, Evimaria Terzi:
Targeted matrix completion. 255-263 - Charalampos Mavroforakis, Dóra Erdös, Mark Crovella, Evimaria Terzi:
Active Positive-Definite Matrix Completion. 264-272 - Christian Böhm, Martin Perdacher, Claudia Plant:
Multi-core K-means. 273-281 - Chang Wei Tan, Geoffrey I. Webb, François Petitjean:
Indexing and classifying gigabytes of time series under time warping. 282-290 - Vishal Kakkar, Shirish K. Shevade, S. Sundararajan, Dinesh Garg:
A Sparse Nonlinear Classifier Design Using AUC Optimization. 291-299 - Ryan R. Curtin:
A Dual-Tree Algorithm for Fast k-means Clustering With Large k. 300-308 - Wilhelmiina Hämäläinen, Geoffrey I. Webb:
Specious rules: an efficient and effective unifying method for removing misleading and uninformative patterns in association rule mining. 309-317 - Yao Zhang, Bijaya Adhikari, Steve T. K. Jan, B. Aditya Prakash:
MeiKe: Influence-based Communities in Networks. 318-326 - Suhang Wang, Jiliang Tang, Charu C. Aggarwal, Yi Chang, Huan Liu:
Signed Network Embedding in Social Media. 327-335 - Esther Galbrun, Behzad Golshan, Aristides Gionis, Evimaria Terzi:
Finding low-tension communities. 336-344 - Marc Mitri, Fragkiskos D. Malliaros, Michalis Vazirgiannis:
Sensitivity of Community Structure to Network Uncertainty. 345-353 - Xuan-Hong Dang, Hongyuan You, Ambuj K. Singh, Scott T. Grafton:
Subnetwork Mining with Spatial and Temporal Smoothness. 354-362 - Hsiang-Fu Yu, Mikhail Bilenko, Chih-Jen Lin:
Selection of Negative Samples for One-class Matrix Factorization. 363-371 - Ziyu Lu, Hui Li, Nikos Mamoulis, David W. Cheung:
HBGG: a Hierarchical Bayesian Geographical Model for Group Recommendation. 372-380 - Chuxu Zhang, Lu Yu, Yan Wang, Chirag Shah, Xiangliang Zhang:
Collaborative User Network Embedding for Social Recommender Systems. 381-389 - Daniel Basaran, Eirini Ntoutsi, Arthur Zimek:
Redundancies in Data and their Effect on the Evaluation of Recommendation Systems: A Case Study on the Amazon Reviews Datasets. 390-398 - Yang Li, Suhang Wang, Tao Yang, Quan Pan, Jiliang Tang:
Price Recommendation on Vacation Rental Websites. 399-407 - Abhinav Mishra, Leman Akoglu:
Ranking in Heterogeneous Networks with Geo-Location Information. 408-416 - Bijaya Adhikari, Yao Zhang, Aditya Bharadwaj, B. Aditya Prakash:
Condensing Temporal Networks using Propagation. 417-425 - Aristides Gionis, Polina Rozenshtein, Nikolaj Tatti, Evimaria Terzi:
Community-aware network sparsification. 426-434 - Leto Peel:
Graph-based semi-supervised learning for relational networks. 435-443 - Jundong Li, Liang Wu, Osmar R. Zaïane, Huan Liu:
Toward Personalized Relational Learning. 444-452 - Daniel Rugeles, Kaiqi Zhao, Gao Cong, Manoranjan Dash, Shonali Krishnaswamy:
Biclustering: An application of Dual Topic Models. 453-461 - Xenophon Evangelopoulos, Austin J. Brockmeier, Tingting Mu, John Yannis Goulermas:
A Graduated Non-Convexity Relaxation for Large Scale Seriation. 462-470 - Arun Reddy Nelakurthi, Hanghang Tong, Ross Maciejewski, Nadya Bliss, Jingrui He:
User-guided Cross-domain Sentiment Classification. 471-479 - Subhabrata Mukherjee, Kashyap Popat, Gerhard Weikum:
Exploring Latent Semantic Factors to Find Useful Product Reviews. 480-488 - Ramakrishnan Kannan, Hyenkyun Woo, Charu C. Aggarwal, Haesun Park:
Outlier Detection for Text Data. 489-497 - Tyler M. Tomita, Mauro Maggioni, Joshua T. Vogelstein:
ROFLMAO: Robust Oblique Forests with Linear MAtrix Operations. 498-506 - Suhang Wang, Yilin Wang, Jiliang Tang, Charu C. Aggarwal, Suhas Ranganath, Huan Liu:
Exploiting Hierarchical Structures for Unsupervised Feature Selection. 507-515 - Lin Chen, Jiliang Tang, Baoxin Li:
Embedded Supervised Feature Selection for Multi-class Data. 516-524 - Kailash Budhathoki, Jilles Vreeken:
Correlation by Compression. 525-533 - Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack, Oluwasanmi Koyejo:
A Deflation Method for Structured Probabilistic PCA. 534-542 - John Boaz Lee, Xiangnan Kong, Yihan Bao, Constance M. Moore:
Identifying Deep Contrasting Networks from Time Series Data: Application to Brain Network Analysis. 543-551 - Sara Morsy, George Karypis:
Cumulative Knowledge-based Regression Models for Next-term Grade Prediction. 552-560 - Miguel Araujo, Miguel Almeida, Jaime Ferreira, Luís Moura Silva, Pedro Bizarro:
BreachRadar: Automatic Detection of Points-of-Compromise. 561-569 - Si Zhang, Dawei Zhou, Mehmet Yigit Yildirim, Scott Alcorn, Jingrui He, Hasan Davulcu, Hanghang Tong:
HiDDen: Hierarchical Dense Subgraph Detection with Application to Financial Fraud Detection. 570-578 - Yao Zhou, Lei Ying, Jingrui He:
MultiC2: an Optimization Framework for Learning from Task and Worker Dual Heterogeneity. 579-587 - Yan Zhao, Xiao Fang, David Simchi-Levi:
Uplift Modeling with Multiple Treatments and General Response Types. 588-596 - Robert S. Pienta, Minsuk Kahng, Zhiyuan Lin, Jilles Vreeken, Partha P. Talukdar, James Abello, Ganesh Parameswaran, Duen Horng Chau:
FACETS: Adaptive Local Exploration of Large Graphs. 597-605 - Fang Jin, Feng Chen, Rupinder Paul Khandpur, Chang-Tien Lu, Naren Ramakrishnan:
Absenteeism Detection in Social Media. 606-614 - Huda Nassar, David F. Gleich:
Multimodal Network Alignment. 615-623 - Jose Cadena, Feng Chen, Anil Vullikanti:
Near-Optimal and Practical Algorithms for Graph Scan Statistics. 624-632 - Xiao Huang, Jundong Li, Xia Hu:
Accelerated Attributed Network Embedding. 633-641 - Yao Zhang, Yun Xiong, Xinyue Liu, Xiangnan Kong, Yangyong Zhu:
Meta-Path Graphical Lasso for Learning Heterogeneous Connectivities. 642-650 - Koray Mancuhan, Chris Clifton:
Statistical Learning Theory Approach for Data Classification with ℓ-diversity. 651-659 - Reinhard Heckel, Michail Vlachos:
Private and Right-Protected Big Data Publication: An Analysis. 660-668 - Michael Hay, Liudmila Elagina, Gerome Miklau:
Differentially Private Rank Aggregation. 669-677 - Shuai Yuan, Pang-Ning Tan, Kendra Spence Cheruvelil, C. Emi Fergus, Nicholas K. Skaff, Patricia A. Soranno:
Hash-Based Feature Learning for Incomplete Continuous-Valued Data. 678-686 - Keerthiram Murugesan, Jaime G. Carbonell:
Multi-Task Multiple Kernel Relationship Learning. 687-695 - Jussi Korpela, Emilia Oikarinen, Kai Puolamäki, Antti Ukkonen:
Multivariate Confidence Intervals. 696-704 - Nayyar Abbas Zaidi, Geoffrey I. Webb:
A Fast Trust-Region Newton Method for Softmax Logistic Regression. 705-713 - Yada Zhu, Jianbo Li, Jingrui He:
Learning from Multi-Modality Multi-Resolution Data: an Optimization Approach. 714-722 - Kohei Miyaguchi, Shin Matsushima, Kenji Yamanishi:
Sparse Graphical Modeling via Stochastic Complexity. 723-731 - Ching-Pei Lee, Po-Wei Wang, Weizhu Chen, Chih-Jen Lin:
Limited-memory Common-directions Method for Distributed Optimization and its Application on Empirical Risk Minimization. 732-740 - Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme:
Automatic Frankensteining: Creating Complex Ensembles Autonomously. 741-749 - Frank Schoeneman, Suchismit Mahapatra, Varun Chandola, Nils Napp, Jaroslaw Zola:
Error Metrics for Learning Reliable Manifolds from Streaming Data. 750-758 - Zhong Chen, Zhide Fang, Wei Fan, Andrea Edwards, Kun Zhang:
CSTG: An Effective Framework for Cost-sensitive Sparse Online Learning. 759-767 - Shujian Yu, Zubin Abraham:
Concept Drift Detection with Hierarchical Hypothesis Testing. 768-776 - Rose Yu, Yaguang Li, Cyrus Shahabi, Ugur Demiryurek, Yan Liu:
Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting. 777-785 - Zongge Liu, Hyun Ah Song, Vladimir Zadorozhny, Christos Faloutsos, Nicholas D. Sidiropoulos:
H-Fuse: Efficient Fusion of Aggregated Historical Data. 786-794 - Apratim Bhattacharyya, Jilles Vreeken:
Efficiently Summarising Event Sequences with Rich Interleaving Patterns. 795-803 - Zhenhui Li, Guanjie Zheng, Amal Agarwal, Lingzhou Xue, Thomas Lauvaux:
Discovery of Causal Time Intervals. 804-812 - Martin P. Seybold:
Robust Map Matching for Heterogeneous Data via Dominance Decompositions. 813-821 - Martin Jankowiak, Manuel Gomez-Rodriguez:
Uncovering the Spatiotemporal Patterns of Collective Social Activity. 822-830 - Nikolaj Tatti:
Discovering bursts revisited: guaranteed optimization of the model parameters. 831-839 - Back Matter. 840-847
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