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 March.

Meta-learning for Size and Fit Recommendation in Fashion
Julia Lasserre (Zalando Research); Saboor Sheikh (Zalando); Evgenii Koriagin (Zalando SE); Urs Bergmann (Zalando Research); Roland Vollgraf (Zalando Research); Reza Shirvany (Zalando SE)

Two-Sample Testing for Event Impacts in Time Series
Erik ScharwŠchter (University of Bonn); Emmanuel MŸller (University of Bonn & Fraunhofer IAIS)

Deep Multi-sphere Support Vector Data Description
Zahra Ghafoori (the University of Melbourne); Christopher Leckie (University of Melbourne)

Cost-Effective and Stable Policy Optimization Algorithm for Uplift Modeling with Multiple Treatments
Yuta Saito (Tokyo Institute of Technology.); Hayato Sakata (So-net Media Networks Corp.); Kazuhide Nakata (Department of Industrial Engineering and Economics, Tokyo Institute of Technology.)

Deep Adversarial Canonical Correlation Analysis
Wenqi FAN (City University of Hong Kong); Yao Ma (Michigan State University); Han Xu (Michigan State University); Xiaorui Liu (Michigan State University); Jianping Wang (City University of Hong Kong); Qing Li (The Hong Kong Polytechnic University ); Jiliang Tang (Michigan State University)

Deep Self-representative Concept Factorization Network for Representation Learning
Yan Zhang (Soochow University); Zhao Zhang (Hefei University of Technology); Zheng Zhang (Harbin Institute of Technology, Shenzhen); Mingbo Zhao (Donghua University); Li Zhang (Soochow University); Zheng-Jun Zha (University of Science and Technology of China); Meng Wang (Hefei University of Technology)

Deep Neural Networks with Knowledge Instillation
Fan Yang (Texas A&M University); Ninghao Liu (Texas A&M University ); Mengnan Du (Texas A&M University); Kaixiong N Zhou (Texas A&M University); Shuiwang Ji (Texas A&M University); Xia Hu (Texas A&M University)

Learning Time-series Shapelets for Optimizing Partial AUC
Akihiro Yamaguchi (Toshiba Corporation)

Knowledge guided diagnosis prediction via graph spatial-temporal network
Yang Li (Xi'an Jiaotong University); Xianli Zhang (Xi'an Jiaotong University); Buyue Qian (Xi'an Jiaotong University); Hui Liu (Xi'an Jiaotong University); Qinghua Zheng (School of Electronic and Information Engineering, Xi'an Jiaotong University)

Convolutional Methods for Predictive Modeling of Geospatial Data
Tyler Wilson (Michigan State University); Pang-Ning Tan (MSU); Lifeng Luo (Michigan State University)

Offline Evaluation of Treatment Assignment Functions with Networked Observational Data
Ruocheng Guo (Arizona State University); Jundong Li (University of Virginia); Huan Liu (Arizona State University)

Lag-Aware Multivariate Time-Series Segmentation
Shigeru Maya (Toshiba Corporation); Shigeru Maya (Toshiba Corporation)

Exploring the Unknown - Query Synthesis in One-Class Active Learning
Adrian Englhardt (Karlsruhe Institute of Technology (KIT)); Klemens Bšhm (Karlsruhe Institute of Technology (KIT))

A Graph-Based Approach for Active Learning in Regression
Hongjing Zhang (UC Davis); S S Ravi (Biocomplexity Institute & Initiative, University of Virginia ); Ian Davidson (UC Davis)

Improved mixing time for k-subgraph sampling
Ryuta Matsuno (Tokyo Institute of Technology); Aristides Gionis (Aalto University)

Two-variable Dual Coordinate Descent Methods for Linear SVM with/without the Bias Term
Chi-Cheng Chiu (National Taiwan University); Pin-Yen Lin (National Taiwan University); Chih-Jen Lin (National Taiwan University)

Rare Disease Prediction by Generating Quality-Assured Electronic Health Records
Fenglong Ma (Pennsylvania State University); Yaqing Wang (SUNY Buffalo); Jing Gao (University at Buffalo); Houping Xiao (Georgia State University); Jing Zhou (Ehealth Inc)

Deep Parametric Model for Discovering Group-cohesive Functional Brain Regions
John Lee (WPI); Xiangnan Kong (Worcester Polytechnic Institute); constance moore (University of Massachusetts Medical School); Nesreen Ahmed (Intel Labs)

Learning a Neural-network-based Representation for Open Set Recognition
Mehadi S Hassen (Florida Institute of Technology); Philip Chan (Florida Institute of Technology, USA)

Finding the Sweet Spot: Batch Selection for One-Class Active Learning
Adrian Englhardt (Karlsruhe Institute of Technology (KIT)); Holger Trittenbach (Karlsruhe Institute of Technology); Dennis Vetter ( Karlsruhe Institute of Technology (KIT)); Klemens Bšhm (Karlsruhe Institute of Technology (KIT))

A Predictive Optimization Framework for Hierarchical Demand Matching
Naoto Ohsaka (NEC Corporation); Tomoya Sakai (NEC); Akihiro Yabe ()

SPADE:Streaming PARAFAC2 DEcompistion for Large Datasets
Ekta Gujral (University of California, Riverside); Georgios Theocharous ("Adobe Research, USA"); Evangelos Papalexakis (UC Riverside)

Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach
JUNNING DENG (Ghent University ); Bo Kang (Ghent University); Jefrey Lijffijt (Ghent University); Tijl De Bie (Ghent University)

Deep Kernel Learning for Clustering
Chieh T Wu (Northeastern); Zulqarnain Q Khan (Northeastern University); Stratis Ioannidis (Northeastern University); Jennifer Dy (Northeastern)

An Advantage Actor-Critic Algorithm with Confidence Exploration for Open Information Extraction
Guiliang Liu (Simon Fraser University); XU LI (Baidu Research); Mingming Sun (Baidu Research); Ping Li (Baidu Research)

BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network
Zhiwei Liu (University of Illinois at Chicago); Mengting Wan (Airbnb); Stephen Guo (Walmart Labs); Kannan Achan (Walmart Labs); Philip S Yu (UIC)

Dual-Attention Recurrent Networks for Affine Registration of Neuroimaging Data
Xin Dai (Worcester polytechnic institute); Xiangnan Kong (Worcester Polytechnic Institute); Xinyue Liu (Worcester Polytechnic Institute); John Lee (WPI); constance moore (University of Massachusetts Medical School)

Vertex-reinforced Random Walk for Network Embedding
Wenyi XIAO (HKUST); Huan Zhao (HKUST); Vincent W. Zheng (WeBank); Yangqiu Song (Hong Kong University of Science and Technology)

Multi-view Semi-supervised Classification using Attention-based Regularization on Coarse-resolution Data
Guruprasad Nayak (University of Minnesota); Rahul Ghosh (University of Minnesota); Varun Mithal (LinkedIn Corporation); Xiaowei Jia (University of Minnesota); Vipin Kumar (University of Minnesota)

Maximizing diversity over clustered data
Guangyi Zhang (Aalto University); Aristides Gionis (Aalto University)

Pattern detection in large temporal graphs using algebraic fingerprints
Suhas Thejaswi (Aalto Univeristy); Aristides Gionis (Aalto University)

Heterogeneous Dual-Task Clustering with Visual-Textual Information
Xiaoqiang Yan (Zhengzhou University); Yiqiao Mao (Zhengzhou University); Shizhe Hu (Zhengzhou University); Yangdong Ye (Zhengzhou University)

What Do Questions Exactly Ask? MFAE: Duplicate Question Identification with Multi-Fusion Asking Emphasis
Rong Zhang (Peking University); Qifei Zhou (Peking University); Bo Wu (Columbia University); Weiping Li (Peking University); Tong Mo (Peking University)

Dual Coordinate-Descent Methods for Linear One-Class SVM and SVDD
Hung-Yi Chou (National Taiwan University ); Pin-Yen Lin (National Taiwan University); Chih-Jen Lin (National Taiwan University)

Fisher Deep Domain Adaptation
Yinghua Zhang (Hong Kong University of Science and Technology); Yu Zhang (HKUST); Ying WEI (Tencent AI Lab); Kun Bai (Tencent Inc); Yangqiu Song (Hong Kong University of Science and Technology); Qiang Yang (Hong Kong UST)

Stacked Mix-Order Graph Convolutional Networks for Collaborative Filtering
Hengrui Zhang (Shanghai Jiao Tong University); Julian McAuley (UCSD)

On Supervised Change Detection in Graph Streams

Representation Learning for Imbalanced Cross-Domain Classification
Lu Cheng (Arizona State University); Ruocheng Guo (Arizona State University); K. Sel?uk Candan (Arizona State University); Huan Liu (Arizona State University)

Efficient and Effective Graph Convolution Networks
Siwu Liu (Stony Brook University); Ji Hwan Park (Brookhaven National Laboratory); Shinjae Yoo (Brookhaven National Laboratory)

ÒNow you see it, now you donÕt!Ó Detecting Suspicious Pattern Absences in Continuous Time Series
Vincent Vercruyssen (KU Leuven); Jesse Davis (KU Leuven); Wannes Meert (KU Leuven)

Optimal Bidding Strategy without Exploration in Real-time Bidding
Aritra Ghosh (University of Massachusetts, Amherst); Saayan Mitra (Adobe); Somdeb Sarkhel (Adobe); Viswanathan Swaminathan (Adobe)

On the Information Unfairness of Social Networks
Zeinab S Jalali (Syracuse University); Weixiang Wang (Syracuse University); Myunghwan Kim (LinkedIn); Hema Raghavan (LinkedIn Corporation)

Hessian based analysis of SGD for Deep Nets: Dynamics and Generalization
Xinyan Li (University of Minnesota); Qilong Gu (University of Minnesota, Twin-); Yingxue Zhou (University of Minnesota); Tiancong Chen (University of Minnesota); Arindam Banerjee (University of Minnesota)

Global-and-Local Aware Data Generation for the Class Imbalance Problem
Wentao Wang (Michigan State University); Suhang Wang (Pennsylvania State University); Wenqi FAN (City University of Hong Kong); Zitao Liu (TAL AI Lab); Jiliang Tang (Michigan State University)

Semantic Discord: Finding Unusual Local Patterns for Time Series
Li Zhang (George Mason University); Yifeng Gao (George Mason University); Jessica Lin (George Mason University)

Identifying Potential Investors with Data Driven Approaches
Bo Yang (University of Minnesota); Kejun Huang (University of Florida); Nicholas Sidiropoulos (University of Virginia)

Residual Core Maximization: An Efficient Algorithm for Maximizing the Size of the k-Core
Ricky Laishram (Syracuse University); A. Erdem Sariyuce (University at Buffalo); Tina Eliassi Rad (Northeastern University); Ali Pinar (Sandia National Laboratories); Sucheta Soundarajan (Syracuse University)

BiGAN: Collaborative Filtering with Bidirectional Generative Adversarial Networks
rui ding (NEU); Guibing Guo (Northeastern University); Xiaochun Yang (Northeastern University); Bowei Chen (Northeastern University); Zhirong Liu (Huawei Noah's Ark Lab); Xiuqiang He (Huawei Noah's Ark Lab)

SSNN: Sentiment Shift Neural Network
Tomoki Ito (The University of Tokyo); Kota Tsubouchi (Yahoo Japan Corporation); Hiroki Sakaji (The University of Tokyo); Tatsuo Yamashita (Yahoo Japan Corporation); _ __ (____)

Multiplex Memory Network for Collaborative Filtering
Xunqiang Jiang (Beijing University of Posts and Telecommunications); Binbin Hu (ant financial); Yuan Fang (Singapore Management University); Chuan Shi (Beijing University of Posts and Telecommunications)

Second-order Optimization for Non-convex Machine Learning: an Empirical Study
Peng Xu (Stanford); Fred Roosta (University of Queensland); Michael Mahoney ("University of California, Berkeley")

Document Clustering Meets Topic Modeling with Word Embeddings
Gianni Costa (ICAR-CNR); Riccardo Ortale (ICAR-CNR)

HYPA: Efficient Detection of Path Anomalies in Time Series Data on Networks
Timothy LaRock (Northeastern University Network Science Institute); Vahan Nanumyan (ETH Zurich); Ingo Scholtes (Univeristy of Wuppertal); Giona Casiraghi (ETH Zurich); Tina Eliassi-Rad (NortheasternUniversity); Frank Schweitzer (ETH Zurich)

Content-Aware Successive Point-of-Interest Recommendation
Buru Chang (Korea University); Yookyung Koh (Korea University); Donghyeon Park (Korea University); Jaewoo Kang (Korea University)

Dissecting Ethereum Blockchain Analytics: What We Learn from Topology and Geometry of Ethereum Graph Ethereum
Yulia R Gel (University of Waterloo); Cuneyt G Akcora (Univ. Manitoba); Umar Islambekov (Bowling Green State University); Murat Kantarcioglu (UT Dallas); Yitao Li (Purdue University); Ekaterina Smirnova (Virginia Commonwealth University)

HIDRA: Head Initialization across Dynamic targets for Robust Architectures
Rafael Rego Drumond (UniversitŠt Hildesheim); Lukas Brinkmeyer (UniversitŠt Hildesheim); Josif Grabocka (University of Hildesheim); Lars Schmidt-Thieme (University of Hildesheim)

A Unified Non-Negative Matrix Factorization Framework for Semi Supervised Learning on Graphs
Anasua Mitra (IIT G); Priyesh Vijayan (McGill university ); Balaraman Ravindran (Indian Institute of Technology, Madras); Srinivasan Parthasarathy (Ohio State University)

Temporal Graph Kernels for Classifying Dissemination Processes
Lutz Oettershagen (University of Bonn); Nils Kriege (TU Dortmund); Christopher Morris (TU Dortmund University); Petra Mutzel (University of Bonn)

Adiabatic Quantum Computing for Max-Sum Diversification
Christian Bauckhage (Fraunhofer IAIS); Rafet Sifa (Fraunhofer IAIS); Stefan Wrobel (Fraunhofer IAIS)

Filling Missing Values on Wearable-Sensory Time Series Data
Suwen Lin (university of notre dame); Xian Wu (University of Notre Dame); Gonzalo Martinez (University of Notre Dame); Nitesh Chawla (Notre Dame)

Well-calibrated and specialized probability estimation trees
Ulf Johansson (Jšnkšping University); Tuwe Lšfstršm (Jšnkšping University)

Bayesian Modeling of Intersectional Fairness: The Variance of Bias
Jimmy Foulds (UMBC); Rashidul Islam (UMBC); Kamrun Naher Keya (UMBC); Shimei Pan (UMBC)

Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling
Arka Daw (Virginia Tech); R. Quinn Thomas (Virginia Tech); Cayelan Carey (Virginia Tech); Jordan Read (United States Geological Survey); Alison Appling (United States Geological Survey); Anuj Karpatne (Virginia Tech)

D2M: Dynamic Defense and Modeling of Adversarial Movement in Networks
Scott Freitas (georgia tech); Andrew Wicker (N/A); Duen Horng Chau (Georgia Institute of Technology); Joshua Neil (Microsoft)

An Instance-Specific Algorithm for Learning the Structure of Causal Bayesian Networks Containing Latent Variables
Fattaneh Jabbari (University of Pittsburgh); Greg Cooper (UPitt)

Detecting Media Self-Censorship without Explicit Training Data
Rongrong Tao (Virginia Tech); Baojian Zhou (SUNY at Albany); Feng Chen (SUNY at Albany); David Mares (University of California at San Diego); Patrick Butler (Virginia Tech); Naren Ramakrishnan (Virginia Tech); Ryan Kennedy (University of Houston)

Features or Shape? Tackling the False Dichotomy of Time Series Classification
Sara Alaee (University of California Riverside); Alireza Abdoli (University of California, Riverside); Christian Shelton (UC Riverside); Amy Murillo (University of California, Riverside); Alec Gerry (University of California, Riverside); Eamonn Keogh (UC Riverside)

Physics-guided Design and Learning of Neural Networks for Predicting Drag Force on Particle Suspensions in Moving Fluids
Nikhil Muralidhar (Virginia Tech); Jie Bu (Virginia Tech); Anuj Karpatne (Virginia Tech ); Naren Ramakrishnan (Virginia Tech); Danish Tafti (Virginia Tech); Ze Cao (Virginia tech)

DANR: Discrepancy-aware Network Regularization
Hongyuan You (UC Santa Barbara); Furkan Kocayusufoglu (UC, Santa Barbara); Ambuj Singh (UC, Santa Barbara)

NSVD: Normalized Singular Value Deviation Reveals Number of Latent Factors in Tensor Decomposition
Georgios Tsitsikas (University of California, Riverside); Evangelos Papalexakis (UC Riverside)

Harmonic Alignment
Jay Stanley (); Scott A Gigante (Yale University); Guy Wolf (UniversitŽ de MontrŽal); Smita Krishnaswamy (Yale University)

On Deep Matrix Tri-Factorization for Mining Vertex-wise Interactions in Multi-Space Attributed Graphs
Yi He (University of Louisiana at Lafayette); Sheng Chen (University of Louisiana at Lafayette); Thu Nguyen (University of Louisiana at Lafayette); Bruce Wade (University of Louisiana at Lafayette); Wu Xindong (Mininglamp Academy of Sciences)

Attention-Aware Answers of the Crowd
Jinzheng Tu (Southwest University); Guoxian Yu (Southwest University, China); Jun Wang (Southwest University); Carlotta Domeniconi (George Mason University); Xiangliang Zhang (" King Abdullah University of Science and Technology, Saudi Arabia")

GRIA: Graphical Regularization for Integrative Analysis
Changgee Chang (University of Pennsylvania); Jihwan Oh (University of Pennsylvania); Qi Long (University of Pennsylvania)

Heavy-Tailed Universality Predicts Trends in Test Accuracies for Very Large Pre-Trained Deep Neural Networks
Michael Mahoney ("University of California, Berkeley"); Charles Martin (Calculation Consulting)