SDM21 Accepted Papers

Accepted Papers

Visualizer: Accepted Papers

Paper titles and author information appears as submitted.

Paper title and author changes will not be made to this page. The online program will reflect the most up-to-date presentation details, and is scheduled for posting in early April 2021.

Sign-aware Perturbations Regression
Zhongnian Li, Tao Zhang, Wei Shao, Songcan Chen, Daoqiang Zhang

Frank-Wolfe algorithm for learning SVM-type multi-category classifiers
Kenya Tajima, Esmeraldo Ronnie Rey S Zara, Yoshihiro Hirohashi, Tsuyoshi Kato

Reconstruction-based Anomaly Detection with Completely Random Forest
Yi-Xuan Xu, Ming Pang, Ji Feng, Kai Ming Ting, Yuan Jiang, Zhi-Hua Zhou

How many winning tickets are there in one DNN? 
Kathrin Grosse, Michael Backes

Mining Easily Understandable Models from Complex Event Logs
Boris Wiegand, Dietrich Klakow, Jilles Vreeken

Deep Neural Network for 3D Surface Segmentation based on Contour Tree Hierarchy
Wenchong He, Arpan Man Sainju, Zhe Jiang, Da Yan

Learning Time-series Shapelets via Supervised Feature Selection
Akihiro Yamaguchi, Ken Ueno

Fair Classification Under Strict Unawareness
Haoyu Wang, Hengtong Zhang, Yaqing Wang, Jing Gao

Provable Distributed Stochastic Gradient Descent with Delayed Updates
Hongchang Gao, Gang Wu, Ryan A Rossi

Disentangled Dynamic Graph Deep Generation
Wenbin Zhang, Liming Zhang, Dieter Pfoser, Zhao Liang

Robust Dual Recurrent Neural Networks for Financial Time Series Prediction
Jiayu He, Matloob Khushi, Tongliang Liu, Nguyen H. Tran

A Fine-grained Graph-based Spatiotemporal Network for Bike Flow Prediction in Bike-sharing Systems
Peiyu Yi, Feihu Huang, Jian Peng

A Neural Hawkes Process Approach for Online Study Behavior Modeling
Lu Jiang, Pengyang Wang, Ke Cheng, Kunpeng Liu, Minghao Yin, Bo Jin, Yanjie Fu

Turning Attacks into Protection: Social Media Privacy Protection Using Adversarial Attacks
Xiaoting Li, Lingwei Chen, Dinghao Wu

Attention-Based Autoregression for Accurate and Efficient Multivariate Time Series Forecasting
Jaemin Yoo, U Kang

Random Features Strengthen Graph Neural Networks
Ryoma Sato, Makoto Yamada, Hisashi Kashima

Learning over Families of Sets - Hypergraph Representation Learning for Higher Order Tasks
Balasubramaniam Srinivasan, Da Zheng, George Karypis

Node Proximity Is All You Need:  A Unified Framework for Proximity-Preserving and Structural Node and Graph Embedding
Jing Zhu, Xingyu Lu, Mark Heimann, Danai Koutra

Refining Network Alignment to Improve Matched Neighborhood Consistency
Mark Heimann, Xiyuan Chen, Fatemeh Vahedian, Danai Koutra

Physics-Guided Recurrent Graph Model for Predicting Flow and Temperature in River Networks
Xiaowei Jia, Jacob Zwart, Jeffery Sadler, Alison Appling, Samantha Oliver, Steven Markstrom, Jared Willard, Shaoming Xu, Michael Steinbach, Jordan Read, Vipin Kumar

UNIANO: robust and efficient anomaly consensus in time series sensitive to cross-correlated anomaly profiles
Leonor Miss Silva, Vasco Manquinho, Rui Henriques

Faster Stochastic Second Order Method for Large-scale Machine Learning Models
Hongchang Gao, Heng Huang

Density of States Graph Kernels
Leo Huang, Andrew Graven, David Bindel

Maximizing Approximately k-Submodular Functions
Leqian Zheng, Hau Chan, Grigorios Loukides, Minming Li

GPU-Accelerated Constraint-Based Causal Structure Learning for Discrete Data
Christopher Hagedorn, Johannes Huegle

Estimating Conditional Mutual Information for Discrete-Continuous Mixtures using Multi-Dimensional Adaptive Histograms
Alexander Marx, Lincen Yang, Matthijs van Leeuwen

Exceptional Model Mining meets Multi-objective Optimization 
Alexandre MILLOT, Jean-Francois Boulicaut, remy cazabet

Temporal-Aware Graph Neural Network for Credit Risk Prediction
Daixin Wang, Zhiqiang Zhang, Jun Zhou, Peng Cui, Jingli Fang, Quanhui Jia, Yanming Fang, Yuan Qi

Adaptive Holding for Online Bottleneck Matching with Delays
Kaixin Wang, Cheng Long, Yongxin Tong, Jie Zhang, Yi Xu

DPGS: Degree-Preserving Graph Summarization
Houquan Zhou, Shenghua Liu, Kyuhan Lee, Kijung Shin, Huawei Shen, Xueqi Cheng

Dynamic Graph Convolutional Networks Using the Tensor M-Product
Osman Asif Malik, Shashanka Ubaru, Lior Horesh, Misha Kilmer, Haim Avron

A Dimensionality-Driven Approach for Unsupervised Out-of-distribution Detection
Qizhou Wang, Sarah Erfani, Christopher Leckie, Michael E. Houle

GraphShop: Graph-based Approach for Shop-type Recommendation
Guoyuan An, Sungeui Yoon, Jaeyoon Kim, Lin Wang, Myoungho Kim

Scalable Graph Synthesis with Adj and 1-Adj
Noseong Park, Jing Liu, Jayoung Kim, Jinsung Jeon, Jaehoon Lee, Jooyeon Lee, Ozlem Uzuner , Sushil Jajodia 

Large-Scale Flight Frequency Optimization with Global Convergence in the US Domestic Air Passenger Markets
Noseong Park, Dongeun Lee, Seunghyun Hwang, Soyoung Kang, Jinsung Jeon, Duanshun Li, Kookjin Lee, Jing Liu

Supervised Deep Patient Representation Learning Framework for Multi-modal Electronic Health Records
Xianli Zhang, Buyue Qian, Yang Li, Yang Liu, Chen Li

TedPar: Temporally Dependent PARAFAC2 Factorization for Phenotype-based Disease Progression Modeling
Kejing Yin, William Cheung, Benjamin C. M. Fung, Jonathan A Poon

Sequence-aware Heterogeneous Graph Neural Collaborative Filtering
Chen Li, Linmei Hu, Chuan Shi, Guojie Song, Yuanfu Lu

Equitable Allocation of Healthcare Resources with Fair Survival Models
Kamrun Naher Keya, Rashidul Islam, Shimei  Pan, Ian  Stockwell, James Foulds

PRESTO: Simple and Scalable Sampling Techniques for the Rigorous Approximation of Temporal Motif Counts
Ilie Sarpe, Fabio Vandin

Scalable Distributed Approximation of Internal Measures for Clustering Evaluation
Federico Altieri, Andrea Pietracaprina, Geppino Pucci, Fabio Vandin

Fairness-aware Agnostic Federated Learning
Wei Du, Depeng Xu, Xintao Wu, Hanghang Tong

Better Short than Greedy: Interpretable Models through Optimal Rule Boosting
Mario Boley, Simon Teshuva, Pierre Le Bodic, Geoffrey I Webb

Towards Learning Outcome Prediction via Modeling Question Explanations and Student Responses
Tianqi Wang, Fenglong Ma, Yaqing Wang, Tang Tang, Longfei Zhang, Jing Gao

HALO: Learning to Prune Neural Networks with Shrinkage
Skyler Seto, Martin Wells, Wenyu Zhang

Contradictory Structure Learning for Semi-supervised Domain Adaptation
Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, YUN FU

Predictive Optimization with Zero-Shot Domain Adaptation
Tomoya Sakai, Naoto Ohsaka

Automated Group-based Feature Selection via Interactive Reinforcement Learning
Wei Fan, Kunpeng Liu, Hao Liu, Dejing Dou, Yanjie Fu

Graph-based Reinforcement Learning for Active Learning in Real Time: An Application in Modeling River Networks
Xiaowei Jia, Beiyu Lin, Jacob Zwart, Jeffery Sadler, Alison Appling, Samantha Oliver, Jordan Read

Discrete Listwise Collaborative Filtering for Fast Recommendation 
Chenghao Liu, Tao Lu, Zhiyong Cheng, Xin Wang, Jianling Sun, Steven Hoi

Inter-Series Attention Model for COVID-19 Forecasting
Xiaoyong Jin, Yu-Xiang Wang, Xifeng Yan

Discovering Reliable Causal Rules
Kailash Budhathoki, Mario Boley, Jilles Vreeken

A Data-Dependent Algorithm for Querying Earth Mover's Distance with Low Doubling Dimensions
Hu Ding, Tan Chen, Fan Yang, Mingyue Wang

MT-STNets: Multi-Task Spatial-Temporal Networks for Multi-Scale Traffic Prediction
Senzhang Wang, Meiyue Zhang, Hao Miao, Philip S Yu

Verifying Tree Ensembles by Reasoning about Potential Instances
Laurens Devos, Wannes Meert, Jesse Davis

A Deep Adversarial Model for Suffix and Remaining Time Prediction of Event Sequences
Farbod Taymouri, Marcello Larosa, Sarah Erfani

Stochastic Time Series Representation for Interval Pattern Mining via Gaussian Processes
Fabian Berns, Christian Beecks

Retrieving Gaussian Process Models of Adaptive Local Complexity for Large-Scale Data
Fabian Berns, Christian Beecks

Heterogeneous Graph Neural Networks for Query-focused Summarization
Jing Ya, Tingwen Liu, Jiangxia Cao, Li Guo

New Approximation Algorithms for Forest Closeness Centrality - for Individual Vertices and Vertex Groups
Alexander van der Grinten, Eugenio Angriman, Maria Predari, Henning Meyerhenke

Efficient Permutation Testing for Significant Sequential Patterns
Sam Pinxteren, Toon Calders

TeX-Graph: Coupled tensor-matrix knowledge-graph embedding for COVID-19 drug repurposing
Charilaos Kanatsoulis, Nicholas Sidiropoulos

Synthesizing Skeletal Motion and Physiological Signals as a Function of a Virtual Human's Actions and Emotions
Bonny Banerjee, Masoumeh Heidari Kapourchali, Murchana Baruah, Mousumi Deb, Kenneth Sakauye, Mette Olufsen

A Practical Online Framework with a Fixed Memory Budget for Extracting Running Video Summaries
Chandrashekhar Lavania, Kai Wei, Rishabh Iyer, Jeff Bilmes

CiNet: Redesigning Deep Neural Networks for Efficient Mobile-Cloud Collaborative Inference
Xin Dai, Xiangnan Kong, Tian Guo, Yixian Huang

Learning Reliable Rules under Class Imbalance
Dimitrios I Diochnos, Theodore Trafalis

Submodular Maximization via Taylor Series Approximation
Gozde Ozcan, Armin Moharrer, Stratis Ioannidis

Deep Multi-Instance Contrastive Learning with Dual Attention for Anomaly Precursor Detection
Dongkuan Xu, Wei Cheng, Jingchao Ni, Dongsheng Luo, Masanao Natsumeda, Dongjin  Song, Bo Zong, Haifeng Chen, Xiang Zhang

POTION: Optimizing Graph Structure for Targeted Diffusion
Sixie Yu, Leo Torres, Scott Alfeld, Tina Eliassi-Rad, Yevgeniy Vorobeychik

PhraseScope:  An Effective and Unsupervised Framework for Mining High Quality Phrases
Omer Anjum, Mohammad Almasri, Wen-Mei Hwu, Jinjun Xiong

Functional Autoencoders for Functional Data Representation Learning
Tsung-Yu Hsieh, Yiwei Sun, Suhang Wang, Vasant Honavar

SUSAN: The Structural Similarity Random Walk Kernel
Janis Kalofolias, Pascal Welke, Jilles Vreeken

Noise-Response Analysis of Deep Neural Networks Quantifies Robustness and Fingerprints Structural Malware 
Dane Taylor, N. Benjamin Erichson, Qixuan Wu, Michael Mahoney

Maximizing Cohesion and Separation in Graph Representation Learning: A Distance-aware Negative Sampling Approach
M. Maruf, Anuj Karpatne

Signature-Based Anomaly Detection in Networks
Charu Aggarwal, Yao Li, Philip S Yu

Multi-Armed Bandit Guided Feature Subspace Exploration
Kunpeng Liu, Haibo Huang, Wei Zhang, Yanjie Fu, Kien Hua

Yet Meta Learning Can Adapt Fast, it Can Also Break Easily
Han Xu, Yaxin Li, Xiaorui Liu, Hui Liu, Jiliang Tang

Deep Multi-type Objects Muli-view Multi-instance Multi-label Learning
Yang Yuanlin, Guoxian Yu, Carlotta Domeniconi, Xiangliang Zhang

Session-based Recommendation with Hypergraph Attention Networks
Jianling Wang, Kaize Ding, Ziwei Zhu, James Caverlee

Unsupervised Selective Manifold Regularized Matrix Factorization
Priya A Mani, Carlotta Domeniconi, Igor Griva  

LDFeRR: A Fuel-efficient Route Recommendation Approach for Long-distance Driving Based on Historical Trajectories
Min Liu, Zhaohui Peng, Xiaohui Yu, Senzhang Wang, Qiao Song

SUMDocS: Surrounding-aware Unsupervised Multiple Document Summarization
Jingjing Tian, Yuning Mao, Jiawei Han

"Misc”-Aware Weakly Supervised Aspect Classification
Fang Guo, Jingbo Shang, Peiran Li

Influencers and the Giant Component: The Fundamental Hardness in Privacy Protection for Socially Contagious Attributes
Aria Rezaei, Jie Gao, Anand Sarwate

Quadratic Residual Networks: A New Class of Neural Networks for Solving Forward and Inverse Problems in Physics Involving PDEs
Jie Bu, Anuj Karpatne

The following papers were accepted for SDM20 but will be presented at SDM21. Paper titles and author information appears as originally submitted, and title and author changes will not be made to this page. However, the online program will reflect the most up-to-date presentation details and is scheduled for posting in early April 2021.

Dissecting Ethereum Blockchain Analytics: What We Learn from Topology and Geometry of the Ethereum Graph?
Yulia R Gel, Cuneyt G Akcora, Umar Islambekov, Murat Kantarcioglu, Yitao Li, Ekaterina Smirnova

Adiabatic Quantum Computing for Max-Sum Diversification
Christian Bauckhage, Rafet Sifa, Stefan Wrobel

Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling
Arka Daw, R. Quinn Thomas, Cayelan Carey, Jordan Read, Alison Appling, Anuj Karpatne

Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach
Junning Deng, Bo Kang, Jefrey Lijffijt, Tijl De Bie

Bayesian Modeling of Intersectional Fairness: The Variance of Bias
Jimmy Foulds, Rashidul Islam, Kamrun Naher Keya, Shimei Pan

Spade: Streaming PARAFAC2 Decompistion for Large Datasets
Ekta Gujral, Georgios Theocharous, Evangelos Papalexakis

Offline Evaluation of Treatment Assignment Functions with Networked Observational Data
Ruocheng Guo, Jundong Li, Huan Liu

Well-Calibrated and Specialized Probability Estimation Trees
Ulf Johansson, Tuwe Lšfstršm

Residual Core Maximization: An Efficient Algorithm for Maximizing the Size of the K-Core
Ricky Laishram, A. Erdem Sariyuce, Tina Eliassi Rad, Ali Pinar, Sucheta Soundarajan

Hypa: Efficient Detection of Path Anomalies in Time Series Data on Networks
Timothy LaRock, Vahan Nanumyan, Ingo Scholtes, Giona Casiraghi, Tina Eliassi-Rad, Frank Schweitzer

Hessian Based Analysis of SGD for Deep Nets: Dynamics and Generalization
Xinyan Li, Qilong Gu, Yingxue Zhou, Tiancong Chen, Arindam Banerjee

Filling Missing Values on Wearable-Sensory Time Series Data
Suwen Lin, Xian Wu, Gonzalo Martinez, Nitesh Chawla

Lag-Aware Multivariate Time-Series Segmentation
Shigeru Maya

Physics-guided Design and Learning of Neural Networks for Predicting Drag Force on Particle Suspensions in Moving Fluid
Nikhil Muralidhar, Jie Bu, Anuj Karpatne, Naren Ramakrishnan, Danish Tafti, Ze Cao

Temporal Graph Kernels for Classifying Dissemination Processes
Lutz Oettershagen, Nils Kriege, Christopher Morris, Petra Mutzel

Second-Order Optimization for Non-Convex Machine Learning: An Empirical Study
Peng Xu, Fred Roosta, Michael Mahoney

Multiplex Memory Network for Collaborative Filtering
Xunqiang Jiang, Binbin Hu, Yuan Fang, Chuan Shi

Detecting Media Self-Censorship Without Explicit Training Data
Rongrong Tao, Baojian Zhou, Feng Chen, David Mares, Patrick Butler, Naren Ramakrishnan, Ryan Kennedy

Pattern detection in large temporal graphs using algebraic fingerprints
Suhas Thejaswi, Aristides Gionis

NSVD: Normalized Singular Value Deviation Reveals Number of Latent Factors in Tensor Decomposition
Georgios Tsitsikas, Evangelos Papalexakis

“Now You See It, Now You Don’t!” Detecting Suspicious Pattern Absences in Continuous Time Series
Vincent Vercruyssen, Jesse Davis, Wannes Meert

Global-and-Local Aware Data Generation for the Class Imbalance Problem
Wentao Wang, Suhang Wang, Wenqi FAN, Zitao Liu, Jiliang Tang

Vertex-Reinforced Random Walk for Network Embedding
Wenyi Xiao, Huan Zhao, Vincent W. Zheng, Yangqiu Song

Learning Time-series Shapelets for Optimizing Partial AUC
Akihiro Yamaguchi

Identifying Potential Investors with Data Driven Approaches
Bo Yang, Kejun Huang, Nicholas Sidiropoulos

Danr: Discrepancy-Aware Network Regularization
Hongyuan You, Furkan Kocayusufoglu, Ambuj Singh

Attention-Aware Answers of the Crowd
Jinzheng Tu, Guoxian Yu, Jun Wang, Carlotta Domeniconi, Xiangliang Zhang

Fisher Deep Domain Adaptation
Yinghua Zhang, Yu Zhang, Ying Wei, Kun Bai, Yangqiu Song, Qiang Yang

Maximizing Diversity over Clustered Data
Guangyi Zhang, Aristides Gionis

A Graph-Based Approach for Active Learning in Regression
Hongjing Zhang, S S Ravi, Ian Davidson

Semantic Discord: Finding Unusual Local Patterns for Time Series
Li Zhang, Yifeng Gao, Jessica Lin

On the Information Unfairness of Social Networks
Zeinab S Jalali, Weixiang Wang, Myunghwan Kim, Hema Raghavan