Session No.	Paper ID	Title	Author	Session
S1	DM464	Self-Attentive Sequential Recommendation	Wang-Cheng Kang and Julian McAuley	Recommender Systems
S1	DM476	Social Recommendation with Missing Not at Random Data	Jiawei Chen, Can Wang, Martin Ester, Qihao Shi, Yan Feng, and Chun Chen	Recommender Systems
S1	DM537	Interactive Unknowns Recommendation in E-Learning Systems	Shan-Yun Teng, Jundong Li, Lo-Pang-Yun Ting, Kun-Ta Chuang, and Huan Liu	Recommender Systems
S1	DM492	Leveraging Hypergraph Random Walk Tag Expansion and User Social Relation for Microblog Recommendation	Huifang Ma, Di Zhang, Weizhong Zhao, Yanru Wang, and Zhongzhi Shi	Recommender Systems
S1	DM502	Exploiting the Sentimental Bias between Ratings and Reviews for Enhancing Recommendation	Yuanbo Xu, Yongjian Yang, Jiayu Han, En Wang, Fuzhen Zhuang, and Hui Xiong	Recommender Systems
S1	DM823	Next Point-of-Interest Recommendation with Temporal and Multi-level Context Attention	Ranzhen Li, Yanyan SHEN, and Yanmin Zhu	Recommender Systems
S2	DM547	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	Semi-supervised & Active Learning
S2	DM1082	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	Semi-supervised & Active Learning
S2	DM287	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	Semi-supervised & Active Learning
S2	DM443	An Efficient Many-Class Active Learning Framework for Knowledge-Rich Domains	Weishi Shi and Qi Yu	Semi-supervised & Active Learning
S2	DM614	Cost Effective Multi-label Active Learning via Querying Subexamples	Xia Chen, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Zhao Li, and Zili Zhang	Semi-supervised & Active Learning
S2	DM633	Query-Efficient Black-Box Attack by Active Learning	Pengcheng Li, Jinfeng Yi, and Lijun Zhang	Semi-supervised & Active Learning
S2	DM818	Active Learning on Heterogeneous Information Networks: A Multi-armed Bandit Approach	Doris Xin, Ahmed El-Kishky, De Liao, Brandon Norick, and Jiawei Han	Semi-supervised & Active Learning
S2	DM860	Semi-Supervised Community Detection Using Structure and Size	Arjun Bakshi, Srinivasan Parthasarathy, and Kannan Srinivasan	Semi-supervised & Active Learning
S2	DM778	FI-GRL: Fast Inductive Graph Representation Learning via Projection-Cost Preservation	Fei Jiang, Lei Zheng, Jin Xu, and Philip S. Yu	Semi-supervised & Active Learning
S3	DM456	Probabilistic Streaming Tensor Decomposition	Yishuai Du, Yimin Zheng, Kuang-chih Lee, and Shandian Zhe	Streaming
S3	DM243	Online Dictionary Learning with Confidence	Shan You, Chang Xu, and Chao Xu	Streaming
S3	DM334	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	Streaming
S3	DM356	Volatility Drift Prediction for Transactional Data Streams	Yun Sing Koh, David Tse Jung Huang, Chris Pearce, and Gillian Dobbie	Streaming
S3	DM928	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	Streaming
S3	DM1126	Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion	Cole Hawkins and Zheng Zhang	Streaming
S4	DM470	Bug Localization via Supervised Topic Modeling	Yaojing Wang, Yuan Yao, Hanghang Tong, Xuan Huo, Ming Li, Feng Xu, and Jian lu	Supervised Learning
S4	DM668	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	Supervised Learning
S4	DM493	Time Series Classification via Manifold Partition Learning	Yuanduo He, Jialiang Pei, Xu Chu, Yasha Wang, Zhu Jin, and Guangju Peng	Supervised Learning
S4	DM916	Neural Sentence-level Sentiment Classification with Heterogeneous Supervision	Zhigang Yuan, Fangzhao Wu, Junxin Liu, Chuhan Wu, Yongfeng Huang, and Xing Xie	Supervised Learning
S4	DM1148	Mixed Bagging: A Novel Ensemble Learning Framework for Supervised Classification based on Instance Hardness	Ahmedul Kabir, Carolina Ruiz, and Sergio Alvarez	Supervised Learning
S4	DM1200	Using Balancing Terms to Avoid Discrimination in Classification	Simon Enni and Ira Assent	Supervised Learning
S4	DM809	Entire regularization path for sparse nonnegative interaction model	Mirai Takayanagi, Yasuo Tabei, and Hiroto Saigo	Supervised Learning
S5	DM891	Towards Interpretation of Recommender Systems with Sorted Explanation Paths	Fan Yang, Ninghao Liu, Suhang Wang, and Xia Hu	Recommender Systems2
S5	DM1049	A Reinforcement Learning Framework for Explainable Recommendation	Xiting Wang, Yiru Chen, Jie Yang, Le Wu, Zhengtao Wu, and Xing Xie	Recommender Systems2
S5	DM1055	Hierarchical Hybrid Feature Model For Top-N Context-Aware Recommendation	Yingpeng Du, Hongzhi Liu, Zhonghai Wu, and Xing Zhang	Recommender Systems2
S5	DM948	Pseudo-Implicit Feedback for Alleviating Data Sparsity in Top-K Recommendation	Yun He, Haochen Chen, Ziwei Zhu, and James Caverlee	Recommender Systems2
S5	DM968	A Knowledge-Enhanced Deep Recommendation Framework Incorporating GAN-based Models	Deqing Yang, Zikai Guo, Ziyi Wang, Junyang Jiang, Yanghua Xiao, and Wei Wang	Recommender Systems2
S5	DM1183	D-CARS: A Declarative Context-Aware Recommender System	Rosni Lumbantoruan, Xiangmin Zhou, Yongli Ren, and Zhifeng Bao	Recommender Systems2
S6	DM232	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	Deep Learning
S6	DM248	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	Deep Learning
S6	DM378	Deep Headline Generation for Clickbait Detection	Kai Shu, Suhang Wang, Thai Le, Dongwon Lee, and Huan Liu	Deep Learning
S6	DM447	Deep Semantic Correlation Learning based Hashing for Multimedia Cross-Modal Retrieval	Xiaolong Gong, Linpeng Huang, and Fuwei Wang	Deep Learning
S6	DM445	DeepDiffuse: Predicting the 'Who' and 'When' in Cascades	Mohammad R Islam, Sathappan Muthiah, Bijaya Adhikari, B. Aditya Prakash, and Naren Ramakrishnan	Deep Learning
S6	DM601	DeepAD: A Deep Learning Based Approach to Stroke-Level Abnormality Detection in Handwritten Chinese Character Recognition	Tie-Qiang Wang and Cheng-Lin Liu	Deep Learning
S7	DM529	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	Urban & Mobility Data
S7	DM1159	apk2vec: Semi-supervised multi-view representation learning for profiling Android applications	CHARLIE SOH, ANNAMALAI NARAYANAN, LIHUI CHEN, YANG LIU, and LIPO WANG	Urban & Mobility Data
S7	DM571	Human-Centric Urban Transit Evaluation and Planning	Guojun Wu, Yanhua Li, Jie Bao, Yu Zheng, Jieping Ye, and Jun Luo	Urban & Mobility Data
S7	DM779	Local Low-Rank Hawkes Processes for Temporal User-Item Interactions	Jin Shang and Mingxuan Sun	Urban & Mobility Data
S7	DM570	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	Urban & Mobility Data
S7	DM654	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	Urban & Mobility Data
S8	DM1174	Adversarially Learned Anomaly Detection	Houssam Zenati, Manon Romain, Chuan-Sheng Foo, Bruno Lecouat, and Vijay Chandrasekhar	Anomalies & Outliers
S8	DM1169	Dynamic Truth Discovery on Numerical Data	Shi Zhi, Fan Yang, Zheyi Zhu, Qi Li, Zhaoran Wang, and Jiawei Han	Anomalies & Outliers
S8	DM732	Semi-supervised anomaly detection with an application to water analytics	Vincent Vercruyssen, Wannes Meert, Gust Verbruggen, Koen Maes, Ruben Bäumer, and Jesse Davis	Anomalies & Outliers
S8	DM277	SedanSpot: Detecting Anomalies in Edge Streams	Dhivya Eswaran and Christos Faloutsos	Anomalies & Outliers
S8	DM391	Robust Distributed Anomaly Detection using Optimal Weighted One-class Random Forests	Yu-Lin Tsou, Hong-Min Chu, Cong Li, and Shao-Wen Yang	Anomalies & Outliers
S8	DM504	DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection	Swee Kiat Lim, Yi Loo, Ngoc-Trung Tran, Ngai-Man Cheung, Gemma Roig, and Yuval Elovici	Anomalies & Outliers
S8	DM652	Learning Semantic Features for Software Defect Prediction by Code Comments Embedding	Xuan Huo, Yang Yang, Ming Li, and De-Chuan Zhan	Anomalies & Outliers
S8	DM763	Outlier Detection in Urban Traffic Flow Distributions	Youcef Djenouri, Arthur Zimek, and Marco Chiarandini	Anomalies & Outliers
S9	DM584	CADEN: A Context-Aware Deep Embedding Network for Financial Opinions Mining	Liang Zhang, Keli Xiao, Hengshu Zhu, Chuanren Liu, Jingyuan Yang, and Bo Jin	Social
S9	DM721	Tell me something my friends do not know: Diversity maximization in social networks	Antonis Matakos and Aristides Gionis	Social
S9	DM526	ResumeNet: A Learning-based Framework for Automatic Resume Quality Assessment	Yong Luo, Huaizheng Zhang, Yongjie Wang, Yonggang Wen, and Xinwen Zhang	Social
S9	DM483	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	Social
S9	DM851	Maximizing the diversity of exposure in a social network	Cigdem Aslay, Antonis Matakos, Esther Galbrun, and Aristides Gionis	Social
S9	DM706	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	Social
S10	DM777	Deep Structure Learning for Fraud Detection	Haibo Wang, Chuan Zhou, Jia Wu, Weizhen Dang, Xingquan Zhu, and Jilong Wang	Deep Learning2
S10	DM1111	Deep Learning based Scalable Inference of Uncertain Opinions	Xujiang Zhao, Feng Chen, and Jin-Hee Cho	Deep Learning2
S10	DM1043	A United Approach to Learning Sparse Attributed Network Embedding	Hao Wang, Enhong Chen, Qi Liu, Tong Xu, and Dongfang Du	Deep Learning2
S10	DM994	Deep Knowledge Tracing and Dynamic Student Classification for Knowledge Tracing	Sein Minn, Yi Yu, Michel Desmarais, Feida Zhu, and Jill-Jenn Vie	Deep Learning2
S10	DM1099	Improving Deep Forest by Confidence Screening	Ming Pang, Kai Ming Ting, Peng Zhao, and Zhi-Hua Zhou	Deep Learning2
S10	DM458	A Machine Reading Comprehension-based Approach for Featured Snippet Extraction	Chen Zhang, Xuanyu Zhang, and Hao Wang	Deep Learning2
S11	DM468	Fast Rectangle Counting on Massive Networks	Rong Zhu, Zhaonian Zou, and Jianzhong Li	Distributed & High Performance Computing
S11	DM701	Enhancing Very Fast Decision Trees with Local Split-Time Predictions	Viktor Losing, Heiko Wersing, and Barbara Hammer	Distributed & High Performance Computing
S11	DM725	Fast Single-Class Classification and the Principle of Logit Separation	Gil Keren, Sivan Sabato, and Björn Schuller	Distributed & High Performance Computing
S11	DM1155	Asynchronous Dual Free Stochastic Dual Coordinate Ascent for Distributed Data Mining	Zhouyuan Huo and Heng Huang	Distributed & High Performance Computing
S11	DM311	Semi-Convex Hull Tree: Fast Nearest Neighbor Queries for Large Scale Data on GPUs	Yewang chen, Da Li, and Nizar Bouguila	Distributed & High Performance Computing
S11	DM531	eOTD: An Efficient Online Tucker Decomposition for Higher Order Tensors	Houping Xiao, Fei Wang, Fenglong Ma, and Jing Gao	Distributed & High Performance Computing
S11	DM977	Fast Tucker Factorization for Large-Scale Tensor Completion	Dongha Lee, Jaehyung Lee, and Hwanjo Yu	Distributed & High Performance Computing
S12	DM230	Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights	Carl Yang, Yichen Feng, Pan Li, Yu Shi, and Jiawei Han	Graphs
S12	DM970	SuperPart: Supervised graph partitioning for record linkage	Russell Reas, Stephen Ash, Robert Barton, and Andrew Borthwick	Graphs
S12	DM986	Integrative Analysis of Patient Health Records and Neuroimages via Memory-based Graph Convolutional Network	Xi Zhang, Jingyuan Chou, and Fei Wang	Graphs
S12	DM1073	A Low Rank Weighted Graph Convolutional Approach to Weather Prediction	Tyler Wilson, Pang-Ning Tan, and Lifeng Luo	Graphs
S12	DM254	Coherent Graphical Lasso for Brain Network Discovery	Hang Yin, Xinyue Liu, and Xiangnan Kong	Graphs
S12	DM293	The HyperKron Graph Model for higher-order features	Nicole Eikmeier, Arjun Ramani, and David Gleich	Graphs
S12	DM1196	Signed Graph Convolutional Network	Tyler Derr and Jiliang Tang	Graphs
S13	DM279	SCRIMP++: Motif Discovery at Interactive Speeds	Yan Zhu, Chin-Chia Michael Yeh, Zachary Zimmerman, Kaveh Kamgar, and Eamonn Keogh	Unsupervised Learning
S13	DM1029	Learning Community Structure with Variational Autoencoder	Jun Jin Choong, Xin Liu, and Tsuyoshi Murata	Unsupervised Learning
S13	DM578	Deep Heterogeneous Autoencoder for Collaborative Filtering	Tianyu Li, Yukun Ma, Jiu Xu, Bjorn Stenger, Chen Liu, and Yu Hirate	Unsupervised Learning
S13	DM682	Online CP Decomposition for Sparse Tensors	Shuo Zhou, Sarah Erfani, and James Bailey	Unsupervised Learning
S13	DM556	Record2Vec: Unsupervised Representation Learning for Structured Records	Adelene Sim and Andrew Borthwick	Unsupervised Learning
S13	DM664	Unsupervised User Identity Linkage via Factoid Embedding	Wei Xie, Xin Mu, Roy Ka-Wei Lee, Feida Zhu, and Ee Peng Lim	Unsupervised Learning
S13	DM927	Imputing Structured Missing Values in Spatial Data with Clustered Adversarial Matrix Factorization	Qi Wang, Pang-Ning Tan, and Jiayu Zhou	Unsupervised Learning
S14	DM1013	Chinese Medical Concept Normalization by Using Text and Comorbidity Network Embedding	Yizhou Zhang, Xiaojun Ma, and Guojie Song	Bio-Medical
S14	DM873	Multi-task Sparse Metric Learning on Measuring Patient Similarity Progression	Qiuling Suo, Weida Zhong, Fenglong Ma, Ye Yuan, Mengdi Huai, and Aidong Zhang	Bio-Medical
S14	DM937	The Impact of Environmental Stressors on Human Trafficking	Sabina Tomkins, Golnoosh Farnadi, Brian Amanatullah, Lise Getoor, and Steven Minton	Bio-Medical
S14	DM516	Diagnosis Prediction via Medical Context Attention Networks Using Deep Generative Modeling	Wonsung Lee, Sungrae Park, Weonyoung Joo, and Il-Chul Moon	Bio-Medical
S14	DM613	Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction	Jianguo Zhang, Ji Wang, Lifang He, Zhao Li, and Philip S. Yu	Bio-Medical
S14	DM1182	Prediction of MicroRNA Subcellular Localization by Using a Sequence-to-Sequence Model	Yiqun Xiao, Jiaxun Cai, Yang Yang, Hai Zhao, and Hongbin Shen	Bio-Medical
S14	DM322	DrugCom: Synergistic Discovery of Drug Combinations using Tensor Decomposition	Huiyuan Chen and Jing Li	Bio-Medical
S15	DM512	DipTransformation: Enhancing the Structure of a Dataset and thereby improving Clustering	Benjamin Schelling and Claudia Plant	Clustering
S15	DM1067	Realization of Random Forest for Real-Time Evaluation through Tree Framing	Sebastian Buschjäger, Kuan-Hsun Chen, Jian-Jia Chen, and Katharina Morik	Clustering
S15	DM298	Partial Multi-View Clustering via Consistent GAN	Qianqian Wang, Zhengming Ding, ZHIQIANG TAO, Quanxue Gao, and Yun Fu	Clustering
S15	DM536	Predicted Edit Distance Based Clustering of Gene Sequences	Sakti Pramanik, AKM Tauhidul Islam, and Shamik Sural	Clustering
S15	DM615	Multiple Co-Clusterings	Xing Wang, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Zhiwen Yu, and Zili Zhang	Clustering
S15	DM852	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	Clustering
S15	DM1173	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	Clustering
S15	DM299	Clustered Lifelong Learning via Representative Task Selection	Gan Sun, Yang Cong, Yu Kong, and Xiaowei Xu	Clustering
S16	DM423	Deep Reinforcement Learning with Knowledge Transfer for Online Rides Order Dispatching	Zhaodong Wang, Zhiwei (Tony) Qin, Xiaocheng Tang, Jieping Ye, and Hongtu Zhu	Transfer Learning
S16	DM462	A General Cross-domain Recommendation Framework via Bayesian Neural Network	Jia He, Rui Liu, Fuzhen Zhuang, Fen Lin, Cheng Niu, and Qing He	Transfer Learning
S16	DM745	Demographic Inference via Knowledge Transfer in Cross-Domain Recommender Systems	Jin Shang, Mingxuan Sun, and Kevyn Collins-Thompson	Transfer Learning
S16	DM665	Uncluttered Domain Sub-similarity Modeling for Transfer Regression	PENGFEI WEI, RAMON SAGARNA, Yiping Ke, and Yew Soon Ong	Transfer Learning
S16	DM1002	Transfer Hawkes Processes with Content Information	Tianbo Li, Pengfei Wei, and Yiping Ke	Transfer Learning
S16	DM1040	T2S: Domain Adaptation via Model-independent Inverse Mapping and Model Reuse	Zhi-Yu Shen and Ming Li	Transfer Learning
S16	DM864	Binarized Attributed Network Embedding	Hong Yang, Shirui Pan, Peng Zhang, Ling Chen, Defu Lian, and Chengqi Zhang	Transfer Learning
S16	DM911	Tracking and Forecasting Dynamics in Crowdfunding: A Basis-Synthesis Approach	Xiaoying Ren, Linli Xu, Tianxiang Zhao, Chen Zhu, Junliang Guo, and Enhong Chen	Transfer Learning
S17	DM242	GINA: Group Gender Identification Using Privacy-Sensitive Audio Data	Jiaxing Shen, Oren Lederman, Jiannong Cao, Florian Berg, Shaojie Tang, and Alex Pentland	Privacy
S17	DM300	Privacy-Preserving Temporal Record Linkage	Thilina Ranbaduge and Peter Christen	Privacy
S17	DM342	Intelligent Salary Benchmarking for Talent Recruitment: A Holistic Matrix Factorization Approach	Qingxin Meng, Hengshu Zhu, Keli Xiao, and Hui Xiong	Privacy
S17	DM541	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	Privacy
S17	DM863	Differentially Private Prescriptive Analytics	Haripriya Harikumar, Santu Rana, Sunil Gupta, Thin Nguyen, Ramachandra Kaimal, and Svetha Venkatesh	Privacy
S17	DM1210	Privacy-Preserving Multi-Task Learning	Kunpeng Liu, Nitish Uplavikar, Wei Jiang, and Yanjie Fu	Privacy
S17	DM1163	Bitcoin Volatility Forecasting with A Glimpse into Buy and Sell Orders	Tian Guo, Albert Bifet, and Nino Antulov-Fantulin	Privacy
S18	DM724	Sequential Pattern Sampling with Norm Constraints	Lamine Diop, Cheikh Talibouya Diop, Arnaud Giacometti, Dominique Li, and Arnaud Soulet	Patterns
S18	DM727	ProSecCo: Progressive Sequence Mining with Convergence Guarantees	Sacha Servan-Schreiber, Matteo Riondato, and Emanuel Zgraggen	Patterns
S18	DM1121	Concept Mining via Embedding	Keqian Li, Hanwen Zha, Yu Su, and Xifeng Yan	Patterns
S18	DM274	Highly Parallel Sequential Pattern Mining on a Heterogeneous Platform	Yu-Heng Hsieh, Chun-Chieh Chen, Hong-Han Shuai, and Ming-Syan Chen	Patterns
S18	DM595	EPAB: Early Pattern Aware Bayesian Model for Social Content Popularity Prediction	Qitian Wu, Chaoqi Yang, Xiaofeng Gao, Peng He, and Guihai Chen	Patterns
S18	DM694	A Variable-Order Regime Switching Model to Identify Significant Patterns in Financial Markets	Philippe Chatigny, Rongbo Chen, Jean-Marc Patenaude, and Shengrui Wang	Patterns
S18	DM1028	Graph Pattern Mining and Learning through User-defined Relations	Carlos Teixeira, Leonardo Cotta, Bruno Ribeiro, and Wagner Meira Jr.	Patterns
S19	DM887	Image-Enhanced Multi-Level Sentence Representation Net for Natural Language Inference	Kun Zhang, Guangyi Lv, Le Wu, Enhong Chen, Qi Liu, and Han Wu	Natural Language Processing
S19	DM672	Prerequisite-Driven Deep Knowledge Tracing	Penghe CHEN, Yu LU, Vincent Zheng, and Yang Bian	Natural Language Processing
S19	DM702	Summarizing Network Processes with Network-constrained Binary Matrix Factorization	Furkan Kocayusufoğlu, Minh Hoang, and Ambuj Singh	Natural Language Processing
S19	DM542	DAPPER: Scaling Dynamic Author Persona Topic Model to Billion Word Corpora	Robert Giaquinto and Arindam Banerjee	Natural Language Processing
S19	DM876	Interpretable Word Embeddings For Medical Domain	Kishlay Jha, Yaqing Wang, Guangxu Xun, and Aidong Zhang	Natural Language Processing
S19	DM718	Enhancing Question Understanding and Representation for Knowledge Base Relation Detection	Zihan Xu, Haitao Zheng, Zuoyou Fu, and Wei Wang	Natural Language Processing
S19	DM1136	NetGist: Learning to generate task-based network summaries	Sorour E. Amiri, Bijaya Adhikari, Aditya Bharadwaj, and B. Aditya Prakash	Natural Language Processing
S19	DM803	Evaluating Top-k Meta Path Queries on Large Heterogeneous Information Networks	Zichen Zhu, Reynold Cheng, Loc Do, Zhipeng Huang, and Haoci Zhang	Natural Language Processing
S20	DM575	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	Sequences & Time Series
S20	DM713	Explainable time series tweaking via irreversible and reversible temporal transformations	Isak Karlsson, Jonathan Rebane, Panagiotis Papapetrou, and Aristides Gionis	Sequences & Time Series
S20	DM921	DE-RNN: Forecasting the probability density function of nonlinear time series	Kyongmin Yeo, Igor Melnyk, and Nam Nguyen	Sequences & Time Series
S20	DM246	TreeGAN: Syntax-Aware Sequence Generation with Generative Adversarial Networks	Xinyue Liu, Xiangnan Kong, Lei Liu, and Kuorong Chiang	Sequences & Time Series
S20	DM252	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	Sequences & Time Series
S20	DM292	Forecasting Wavelet Transformed Time Series with Attentive Neural Networks	Yi Zhao, Yanyan SHEN, Yanmin Zhu, and Junjie Yao	Sequences & Time Series
S20	DM723	Finding Maximal Significant Linear Representation between Long Time Series	Jiaye Wu, Yang Wang, Peng Wang, Jian Pei, and Wei Wang	Sequences & Time Series
S20	DM1128	A Unified Theory and the Solution of the Mobile Sequential Recommendation Problem	Zeyang Ye, Keli Xiao, and Yuefan Deng	Sequences & Time Series
S21	DM611	SINE: Scalable Incomplete Network Embedding	Daokun Zhang, Jie Yin, Xingquan Zhu, and Chengqi Zhang	Web
S21	DM328	Network Kronecker Hull	Shengmin Jin and Reza Zafarani	Web
S21	DM255	Billion-scale Network Embedding with Iterative Random Projection	Ziwei Zhang, Peng Cui, Haoyang Li, Xiao Wang, and Wenwu Zhu	Web
S21	DM726	Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator	Zhiqian Chen, Feng Chen, Rongjie Lai, Xuchao Zhang, and Chang-Tien Lu	Web
S21	DM419	Distribution Preserving Multi-Task Regression for Spatio-Temporal Data	Xi Liu, Pang-Ning Tan, Zubin Abraham, Lifeng Luo, and Pouyan Hatami	Web
S21	DM752	HHNE: Heterogeneous Hyper-Network Embedding	Inci M Baytas, Cao Xiao, Fei Wang, Anil K. Jain, and Jiayu Zhou	Web
S21	DM1031	Multi-level hypothesis testing for populations of heterogeneous networks	Guilherme Gomes, Jennifer Neville, and Vinayak Rao	Web
S22	DM843	Finding events in temporal networks: Segmentation meets densest-subgraph discovery	Polina Rozenshtein, Francesco Bonchi, Aristides Gionis, Mauro Sozio, and Nikolaj Tatti	Events & Social
S22	DM1070	On Multi-Query Local Community Detection	Yuchen Bian, Yaowei Yan, Wei Cheng, Wei Wang, Dongsheng Luo, and Xiang Zhang	Events & Social
S22	DM884	Learning Sequential Behavior Representations for Fraud Detection	Jia Guo, Guannan Liu, Yuan Zuo, and Junjie Wu	Events & Social
S22	DM272	An Integrated Model for Crime Prediction Using Temporal and Spatial Factors	Fei Yi, Zhiwen Yu, Fuzhen Zhuang, Xiao Zhang, Bin Guo, and Hui Xiong	Events & Social
S22	DM304	A Harmonic Motif Modularity Approach for Multi-layer Network Community Detection	Ling Huang, Chang-Dong Wang, and Hong-Yang Chao	Events & Social
S22	DM1026	Adaptive Affinity Learning for Accurate Community Detection	Fanghua Ye, Shenghui Li, Zhiwei Lin, Chuan Chen, and Zibin Zheng	Events & Social
S22	DM833	Time Discounting Convolution for Event Sequences with Ambiguous Timestamps	Takayuki Katsuki, Takayuki Osogami, Masaki Ono, Akira Koseki, Michiharu Kudo, Masaki Makino, and Atsushi Suzuki	Events & Social
S23	DM226	Incomplete Label Uncertainty Estimation for Petition Victory Prediction with Dynamic Features	Junxiang Wang, Yuyang Gao, Andreas Züfle, Jingyuan Yang, and Liang Zhao	Feature Selection
S23	DM1003	EDLT: Enabling Deep Learning for Generic Data Classification	Huimei Han, Xingquan Zhu, and Ying Li	Feature Selection
S23	DM669	Collaborative Translational Metric Learning	Chanyoung Park, Donghyun Kim, Xing Xie, and Hwanjo Yu	Feature Selection
S23	DM714	Imbalanced Augmented Class Learning with Unlabeled Data by Label Confidence Propagation	Si-Yu Ding, Xu-Ying Liu, and Min-Ling Zhang	Feature Selection
S23	DM345	Multi-View Feature Selection Plus Multi-View Discriminant Analysis: A Complete Multi-View Fisher Discriminant Framework for Heterogeneous Face Recognition	Jie Gui and Ping Li	Feature Selection
S23	DM511	Deep Discriminative Features Learning and Sampling for Imbalanced Data Problem	Yi-Hsun Liu, Chien-Liang Liu, and Vincent Tseng	Feature Selection
S23	DM1127	Robust Regression via Online Feature Selection under Adversarial Data Corruption	Xuchao Zhang, Shuo Lei, Liang Zhao, Arnold Boedihardjo, and Chang-Tien Lu	Feature Selection
S24	DM980	LEEM: Lean Elastic EM for Gaussian Mixture Model via Bounds-Based Filtering	Shuai Yang and Xipeng Shen	Machine Learning
S24	DM862	Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms	Panagiotis Mandros, Mario Boley, and Jilles Vreeken	Machine Learning
S24	DM914	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	Machine Learning
S24	DM446	Spatial Contextualization for Closed Itemset Mining	Altobelli Mantuan and Leandro Fernandes	Machine Learning
S24	DM482	Heterogeneous Data Integration by Learning to Rerank Schema Matches	Avigdor Gal, Haggai Roitman, and Roee Shraga	Machine Learning
S24	DM748	Accurate Causal Inference on Discrete Data	Kailash Budhathoki and Jilles Vreeken	Machine Learning
S24	DM675	Confident Kernel Sparse Coding and Dictionary Learning	Babak Hosseini and Barbara Hammer	Machine Learning
S25	DM588	Cross-Domain Labeled LDA for Text Classification	Baoyu Jing, Chenwei Lu, Deqing Wang, Fuzhen Zhuang, and Cheng Niu	Text
S25	DM867	ASTM: An Attentional Segmentation based Topic Model for Short Texts	Jiamiao Wang, Ling Chen, Lu Qin, and Xindong Wu	Text
S25	DM350	Utilizing In-Store Sensors for Revisit Prediction	Sundong Kim and Jae-Gil Lee	Text
S25	DM1124	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	Text
S25	DM1024	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	Text
S25	DM1037	Text segmentation on multilabel documents: A distant supervised approach	Saurav Manchanda and George Karypis	Text
S25	DM1050	Discovering Topical Interactions in Text-based Cascades using Hidden Markov Hawkes Processes	Jayesh Choudhari, Anirban Dasgupta, Indrajit Bhattacharya, and Srikanta Bedathur	Text
S26	DM528	Synthetic oversampling with the majority class: A new perspective on handling extreme imbalance	Shiven Sharma, Colin Bellinger, Bartosz Krawczyk, Nathalie Japkowicz, and Osmar Zaïane	Theory
S26	DM551	Collapsed Variational Inference for Nonparametric Bayesian Group Factor Analysis	Sikun Yang and Heinz Koeppl	Theory
S26	DM739	Zero-Shot Learning: An Energy based Approach	Tianxiang Zhao, Guiquan Liu, Le Wu, and Chao Ma	Theory
S26	DM834	Robust Cascade Reconstruction by Steiner Tree Sampling	Han Xiao, Cigdem Aslay, and Aristides Gionis	Theory
S26	DM278	Sparse Non-Linear CCA through Hilbert-Schmidt Independence Criterion	Viivi Uurtio, Sahely Bhadra, and Juho Rousu	Theory
S26	DM610	Superlinear Convergence of Randomized Block Lanczos Algorithm	Qiaochu Yuan, Ming Gu, and Bo Li	Theory
S26	DM642	Robust Densest Subgraph Discovery	Atsushi Miyauchi and Akiko Takeda	Theory
S27	DM710	Multi-Label Answer Aggregation based on Joint Matrix Factorization	Jinzheng Tu, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Guoqiang Xiao, and Maozu Guo	Multi-Label Learning
S27	DM728	Independent Feature and Label Components for Multi-label Classification	Yong-Jian Zhong, Chang Xu, Bo Du, and Lefei Zhang	Multi-Label Learning
S27	DM730	Multi-Label Learning with Label Enhancement	Ruifeng Shao, Ning Xu, and Xin Geng	Multi-Label Learning
S27	DM767	Multi-Label Adversarial Perturbations	Qingquan Song, Haifeng Jin, Xiao Huang, and Xia Hu	Multi-Label Learning
S27	DM1008	Estimating Latent Relative Labeling Importances for Multi-Label Learning	Shuo He, Lei Feng, and Li Li	Multi-Label Learning
S27	DM1048	Feature-induced Partial Multi-label Learning	Guoxian Yu, Xia Chen, Carlotta Domeniconi, Jun Wang, Zhao Li, Zili Zhang, and Xindong Wu	Multi-Label Learning