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ORCID25th KDD 2019: Anchorage, AK, USA
- Ankur Teredesai, Vipin Kumar, Ying Li, Rómer Rosales, Evimaria Terzi, George Karypis
:
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019. ACM 2019, ISBN 978-1-4503-6201-6
Keynote Talks
- Cynthia Rudin:
Do Simpler Models Exist and How Can We Find Them? 1-2 - Peter Lee:
The Unreasonable Effectiveness, and Difficulty, of Data in Healthcare. 3-4
Research Track Papers
- Sho Inaba, Carl Tony Fakhry, Rahul V. Kulkarni, Kourosh Zarringhalam:
A Free Energy Based Approach for Distance Metric Learning. 5-13 - Qingxin Meng, Hengshu Zhu, Keli Xiao, Le Zhang, Hui Xiong:
A Hierarchical Career-Path-Aware Neural Network for Job Mobility Prediction. 14-24 - Pinghui Wang, Yiyan Qi, Yuanming Zhang, Qiaozhu Zhai, Chenxu Wang, John C. S. Lui, Xiaohong Guan:
A Memory-Efficient Sketch Method for Estimating High Similarities in Streaming Sets. 25-33 - Bo Wang, Minghui Qiu, Xisen Wang, Yaliang Li, Yu Gong, Xiaoyi Zeng, Jun Huang, Bo Zheng, Deng Cai, Jingren Zhou:
A Minimax Game for Instance based Selective Transfer Learning. 34-43 - Yuchao Liu, Ery Arias-Castro:
A Multiscale Scan Statistic for Adaptive Submatrix Localization. 44-53 - Elias Chaibub Neto, Abhishek Pratap, Thanneer M. Perumal, Meghasyam Tummalacherla, Brian M. Bot, Lara M. Mangravite, Larsson Omberg:
A Permutation Approach to Assess Confounding in Machine Learning Applications for Digital Health. 54-64 - Yifan Hou, Hongzhi Chen, Changji Li, James Cheng, Ming-Chang Yang:
A Representation Learning Framework for Property Graphs. 65-73 - Yang Yang, Da-Wei Zhou, De-Chuan Zhan, Hui Xiong, Yuan Jiang:
Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability. 74-82 - Deng-Bao Wang, Li Li, Min-Ling Zhang:
Adaptive Graph Guided Disambiguation for Partial Label Learning. 83-91 - Jundong Li, Ruocheng Guo, Chenghao Liu, Huan Liu:
Adaptive Unsupervised Feature Selection on Attributed Networks. 92-100 - Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner:
Adaptive-Halting Policy Network for Early Classification. 101-110 - Junxiang Wang, Fuxun Yu, Xiang Chen, Liang Zhao:
ADMM for Efficient Deep Learning with Global Convergence. 111-119 - Binbin Hu, Yuan Fang, Chuan Shi:
Adversarial Learning on Heterogeneous Information Networks. 120-129 - Pengyang Wang, Yanjie Fu, Hui Xiong, Xiaolin Li:
Adversarial Substructured Representation Learning for Mobile User Profiling. 130-138 - Xiang Zhang, Lina Yao, Feng Yuan:
Adversarial Variational Embedding for Robust Semi-supervised Learning. 139-147 - Dmitrii Avdiukhin, Slobodan Mitrovic, Grigory Yaroslavtsev, Samson Zhou:
Adversarially Robust Submodular Maximization under Knapsack Constraints. 148-156 - Tong Yu, Yilin Shen, Hongxia Jin:
A Visual Dialog Augmented Interactive Recommender System. 157-165 - Ben Goodrich, Vinay Rao, Peter J. Liu, Mohammad Saleh:
Assessing The Factual Accuracy of Generated Text. 166-175 - Cong Fu, Yonghui Zhang, Deng Cai, Xiang Ren:
AtSNE: Efficient and Robust Visualization on GPU through Hierarchical Optimization. 176-186 - Sheng Guan, Hanchao Ma, Yinghui Wu:
Attribute-Driven Backbone Discovery. 187-195 - Congzheng Song, Vitaly Shmatikov:
Auditing Data Provenance in Text-Generation Models. 196-206 - Kunpeng Liu, Yanjie Fu, Pengfei Wang, Le Wu, Rui Bo, Xiaolin Li:
Automating Feature Subspace Exploration via Multi-Agent Reinforcement Learning. 207-215 - Ke Tu, Jianxin Ma, Peng Cui, Jian Pei, Wenwu Zhu:
AutoNE: Hyperparameter Optimization for Massive Network Embedding. 216-225 - Xuezhou Zhang, Sarah Tan, Paul Koch, Yin Lou, Urszula Chajewska, Rich Caruana:
Axiomatic Interpretability for Multiclass Additive Models. 226-234 - Wenyi Xiao, Huan Zhao, Haojie Pan, Yangqiu Song, Vincent W. Zheng, Qiang Yang:
Beyond Personalization: Social Content Recommendation for Creator Equality and Consumer Satisfaction. 235-245 - Daniel Zügner, Stephan Günnemann:
Certifiable Robustness and Robust Training for Graph Convolutional Networks. 246-256 - Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh:
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks. 257-266 - Sara Ahmadian, Alessandro Epasto, Ravi Kumar, Mohammad Mahdian:
Clustering without Over-Representation. 267-275 - Hongchang Gao, Jian Pei, Heng Huang:
Conditional Random Field Enhanced Graph Convolutional Neural Networks. 276-284 - Silu Huang, Jialu Liu, Flip Korn, Xuezhi Wang, You Wu, Dale Markowitz, Cong Yu:
Contextual Fact Ranking and Its Applications in Table Synthesis and Compression. 285-293 - Anes Bendimerad, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie:
Contrastive Antichains in Hierarchies. 294-304 - Junchen Ye, Leilei Sun, Bowen Du, Yanjie Fu, Xinran Tong, Hui Xiong:
Co-Prediction of Multiple Transportation Demands Based on Deep Spatio-Temporal Neural Network. 305-313 - Yanhao Wang, Yuchen Li, Kian-Lee Tan:
Coresets for Minimum Enclosing Balls over Sliding Windows. 314-323 - Hanpeng Liu, Yaguang Li, Michael Tsang, Yan Liu:
CoSTCo: A Neural Tensor Completion Model for Sparse Tensors. 324-334 - Qingquan Song, Shiyu Chang, Xia Hu:
Coupled Variational Recurrent Collaborative Filtering. 335-343 - Donghua Liu, Jing Li, Bo Du, Jun Chang, Rong Gao:
DAML: Dual Attention Mutual Learning between Ratings and Reviews for Item Recommendation. 344-352 - Guansong Pang, Chunhua Shen, Anton van den Hengel:
Deep Anomaly Detection with Deviation Networks. 353-362 - Kan Ren, Jiarui Qin, Lei Zheng, Zhengyu Yang, Weinan Zhang, Yong Yu:
Deep Landscape Forecasting for Real-time Bidding Advertising. 363-372 - Maya Okawa, Tomoharu Iwata, Takeshi Kurashima, Yusuke Tanaka, Hiroyuki Toda, Naonori Ueda:
Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information. 373-383 - Guolin Ke, Zhenhui Xu, Jia Zhang, Jiang Bian, Tie-Yan Liu:
DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks. 384-394 - Kai Shu, Limeng Cui, Suhang Wang, Dongwon Lee, Huan Liu:
dEFEND: Explainable Fake News Detection. 395-405 - Jun Wu, Jingrui He, Jiejun Xu:
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification. 406-415 - Jing-Han Wu, Min-Ling Zhang:
Disambiguation Enabled Linear Discriminant Analysis for Partial Label Dimensionality Reduction. 416-424 - Michael Doron, Idan Segev, Dafna Shahaf:
Discovering Unexpected Local Nonlinear Interactions in Scientific Black-box Models. 425-435 - Baojian Zhou, Feng Chen, Yiming Ying:
Dual Averaging Method for Online Graph-structured Sparsity. 436-446 - Qitian Wu, Yirui Gao, Xiaofeng Gao, Paul Weng, Guihai Chen:
Dual Sequential Prediction Models Linking Sequential Recommendation and Information Dissemination. 447-457 - Yasuko Matsubara, Yasushi Sakurai:
Dynamic Modeling and Forecasting of Time-evolving Data Streams. 458-468 - Chengxi Zang, Peng Cui, Wenwu Zhu, Fei Wang:
Dynamical Origins of Distribution Functions. 469-478 - Pei-Zhen Li, Ling Huang, Chang-Dong Wang, Jian-Huang Lai:
EdMot: An Edge Enhancement Approach for Motif-aware Community Detection. 479-487 - Lisi Chen, Shuo Shang, Christian S. Jensen, Bin Yao, Zhiwei Zhang, Ling Shao:
Effective and Efficient Reuse of Past Travel Behavior for Route Recommendation. 488-498 - Zheng Wang, Cheng Long, Gao Cong, Ce Ju:
Effective and Efficient Sports Play Retrieval with Deep Representation Learning. 499-509 - Yexin Li, Yu Zheng, Qiang Yang:
Efficient and Effective Express via Contextual Cooperative Reinforcement Learning. 510-519 - Lingfei Wu, Ian En-Hsu Yen, Siyu Huo, Liang Zhao, Kun Xu, Liang Ma, Shouling Ji, Charu C. Aggarwal:
Efficient Global String Kernel with Random Features: Beyond Counting Substructures. 520-528 - Lijun Chang:
Efficient Maximum Clique Computation over Large Sparse Graphs. 529-538 - Jingyuan Wang, Ning Wu, Wayne Xin Zhao, Fanzhang Peng, Xin Lin:
Empowering A* Search Algorithms with Neural Networks for Personalized Route Recommendation. 539-547 - Qinyong Wang, Hongzhi Yin, Hao Wang, Quoc Viet Hung Nguyen, Zi Huang, Lizhen Cui:
Enhancing Collaborative Filtering with Generative Augmentation. 548-556 - Shibo Yao, Dantong Yu, Keli Xiao:
Enhancing Domain Word Embedding via Latent Semantic Imputation. 557-565 - Wenjie Shang, Yang Yu, Qingyang Li, Zhiwei (Tony) Qin, Yiping Meng, Jieping Ye:
Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation. 566-576 - Bijaya Adhikari, Xinfeng Xu, Naren Ramakrishnan, B. Aditya Prakash:
EpiDeep: Exploiting Embeddings for Epidemic Forecasting. 577-586 - Kirill Paramonov, Dmitry Shemetov, James Sharpnack:
Estimating Graphlet Statistics via Lifting. 587-595 - Namyong Park, Andrey Kan, Xin Luna Dong, Tong Zhao, Christos Faloutsos:
Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks. 596-606 - Songshan Yang, Jiawei Wen, Xiang Zhan, Daniel Kifer:
ET-Lasso: A New Efficient Tuning of Lasso-type Regularization for High-Dimensional Data. 607-616 - Yu Gong, Yu Zhu, Lu Duan, Qingwen Liu, Ziyu Guan, Fei Sun, Wenwu Ou, Kenny Q. Zhu:
Exact-K Recommendation via Maximal Clique Optimization. 617-626 - Qi Liu, Shiwei Tong, Chuanren Liu, Hongke Zhao, Enhong Chen, Haiping Ma, Shijin Wang:
Exploiting Cognitive Structure for Adaptive Learning. 627-635 - Qingyun Wu, Zhige Li, Huazheng Wang, Wei Chen, Hongning Wang:
Factorization Bandits for Online Influence Maximization. 636-646 - Minji Yoon, Bryan Hooi, Kijung Shin, Christos Faloutsos:
Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach. 647-657 - Chi Wang, Bailu Ding:
Fast Approximation of Empirical Entropy via Subsampling. 658-667 - Haoyang Li, Peng Cui, Chengxi Zang, Tianyang Zhang, Wenwu Zhu, Yishi Lin:
Fates of Microscopic Social Ecosystems: Keep Alive or Dead? 668-676 - Victor Amelkin, Ambuj K. Singh:
Fighting Opinion Control in Social Networks via Link Recommendation. 677-685 - Nikita Klyuchnikov, Davide Mottin, Georgia Koutrika, Emmanuel Müller, Panagiotis Karras:
Figuring out the User in a Few Steps: Bayesian Multifidelity Active Search with Cokriging. 686-695 - Hao Zou, Kun Kuang, Boqi Chen, Peixuan Chen, Peng Cui:
Focused Context Balancing for Robust Offline Policy Evaluation. 696-704 - Peng Han, Peng Yang, Peilin Zhao, Shuo Shang, Yong Liu, Jiayu Zhou, Xin Gao, Panos Kalnis:
GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization. 705-713 - Nicholas Monath, Manzil Zaheer, Daniel Silva, Andrew McCallum, Amr Ahmed:
Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. 714-722 - Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang:
Graph Convolutional Networks with EigenPooling. 723-731 - Xiao Huang, Qingquan Song, Yuening Li, Xia Hu:
Graph Recurrent Networks With Attributed Random Walks. 732-740 - Hongyang Gao, Shuiwang Ji:
Graph Representation Learning via Hard and Channel-Wise Attention Networks. 741-749 - Kien Do, Truyen Tran, Svetha Venkatesh:
Graph Transformation Policy Network for Chemical Reaction Prediction. 750-760 - Junteng Jia, Michael T. Schaub, Santiago Segarra, Austin R. Benson:
Graph-based Semi-Supervised & Active Learning for Edge Flows. 761-771 - Yujun Yan, Jiong Zhu, Marlena Duda, Eric Solarz, Chandra Sekhar Sripada, Danai Koutra:
GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data. 772-782 - Changping Meng, Jiasen Yang, Bruno Ribeiro, Jennifer Neville:
HATS: A Hierarchical Sequence-Attention Framework for Inductive Set-of-Sets Embeddings. 783-792 - Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami, Nitesh V. Chawla:
Heterogeneous Graph Neural Network. 793-803 - Zhe Jiang, Arpan Man Sainju:
Hidden Markov Contour Tree: A Spatial Structured Model for Hydrological Applications. 804-813 - Yue Cui, Liwei Deng, Yan Zhao, Bin Yao, Vincent W. Zheng, Kai Zheng:
Hidden POI Ranking with Spatial Crowdsourcing. 814-824 - Chen Ma, Peng Kang, Xue Liu:
Hierarchical Gating Networks for Sequential Recommendation. 825-833 - Hongliang Fei, Shulong Tan, Ping Li:
Hierarchical Multi-Task Word Embedding Learning for Synonym Prediction. 834-842 - Kishlay Jha, Guangxu Xun, Yaqing Wang, Aidong Zhang:
Hypothesis Generation From Text Based On Co-Evolution Of Biomedical Concepts. 843-851 - Alexander Marx, Jilles Vreeken:
Identifiability of Cause and Effect using Regularized Regression. 852-861 - Yunzhe Jia, James Bailey, Kotagiri Ramamohanarao, Christopher Leckie, Michael E. Houle:
Improving the Quality of Explanations with Local Embedding Perturbations. 875-884 - Weiyu Cheng, Yanyan Shen, Linpeng Huang, Yanmin Zhu:
Incorporating Interpretability into Latent Factor Models via Fast Influence Analysis. 885-893 - Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu:
Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding. 894-902 - Yao Ming, Panpan Xu, Huamin Qu, Liu Ren:
Interpretable and Steerable Sequence Learning via Prototypes. 903-913 - Rui Yan, Ran Le, Yang Song, Tao Zhang, Xiangliang Zhang, Dongyan Zhao:
Interview Choice Reveals Your Preference on the Market: To Improve Job-Resume Matching through Profiling Memories. 914-922 - Mengyang Liu, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma:
Investigating Cognitive Effects in Session-level Search User Satisfaction. 923-931 - Ninghao Liu, Qiaoyu Tan, Yuening Li, Hongxia Yang, Jingren Zhou, Xia Hu:
Is a Single Vector Enough?: Exploring Node Polysemy for Network Embedding. 932-940 - Bi-Cun Xu, Kai Ming Ting, Zhi-Hua Zhou:
Isolation Set-Kernel and Its Application to Multi-Instance Learning. 941-949 - Xiang Wang, Xiangnan He, Yixin Cao, Meng Liu, Tat-Seng Chua:
KGAT: Knowledge Graph Attention Network for Recommendation. 950-958 - Feiping Nie, Cheng-Long Wang, Xuelong Li:
K-Multiple-Means: A Multiple-Means Clustering Method with Specified K Clusters. 959-967 - Hongwei Wang, Fuzheng Zhang, Mengdi Zhang, Jure Leskovec, Miao Zhao, Wenjie Li, Zhongyuan Wang:
Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems. 968-977 - Yihong Chen, Bei Chen, Xiangnan He, Chen Gao, Yong Li, Jian-Guang Lou, Yue Wang:
λOpt: Learn to Regularize Recommender Models in Finer Levels. 978-986 - Di Jin, Ryan A. Rossi, Eunyee Koh, Sungchul Kim, Anup Rao, Danai Koutra:
Latent Network Summarization: Bridging Network Embedding and Summarization. 987-997 - Ming-Kun Xie, Sheng-Jun Huang:
Learning Class-Conditional GANs with Active Sampling. 998-1006 - Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Learning Dynamic Context Graphs for Predicting Social Events. 1007-1016 - Zhenyu Zhang, Peng Zhao, Yuan Jiang, Zhi-Hua Zhou:
Learning from Incomplete and Inaccurate Supervision. 1017-1025 - Tomoki Yoshida, Ichiro Takeuchi, Masayuki Karasuyama:
Learning Interpretable Metric between Graphs: Convex Formulation and Computation with Graph Mining. 1026-1036 - Zhicheng He, Jie Liu, Na Li, Yalou Huang:
Learning Network-to-Network Model for Content-rich Network Embedding. 1037-1045 - Pinghua Xu, Wenbin Hu, Jia Wu, Bo Du:
Link Prediction with Signed Latent Factors in Signed Social Networks. 1046-1054 - Zhiqiang Tao, Sheng Li, Zhaowen Wang, Chen Fang, Longqi Yang, Handong Zhao, Yun Fu:
Log2Intent: Towards Interpretable User Modeling via Recurrent Semantics Memory Unit. 1055-1063 - Hao Wang, Tong Xu, Qi Liu, Defu Lian, Enhong Chen, Dongfang Du, Han Wu, Wen Su:
MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network. 1064-1072 - Hoyeop Lee, Jinbae Im, Seongwon Jang, Hyunsouk Cho, Sehee Chung:
MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation. 1073-1082 - Hanwen Zha, Wenhu Chen, Keqian Li, Xifeng Yan:
Mining Algorithm Roadmap in Scientific Publications. 1083-1092 - Haoyu Zhang, Qin Zhang:
MinJoin: Efficient Edit Similarity Joins via Local Hash Minima. 1093-1103 - Hemank Lamba, Neil Shah:
Modeling Dwell Time Engagement on Visual Multimedia. 1104-1113 - Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, Xiangnan He:
Modeling Extreme Events in Time Series Prediction. 1114-1122 - Jiejie Zhao, Bowen Du, Leilei Sun, Fuzhen Zhuang, Weifeng Lv, Hui Xiong:
Multiple Relational Attention Network for Multi-task Learning. 1123-1131 - Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme:
Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings. 1132-1140 - Chang Li, Dongjin Song, Dacheng Tao:
Multi-task Recurrent Neural Networks and Higher-order Markov Random Fields for Stock Price Movement Prediction: Multi-task RNN and Higer-order MRFs for Stock Price Classification. 1141-1151 - Kun Dong, Austin R. Benson, David Bindel:
Network Density of States. 1152-1161 - Dingqi Yang, Paolo Rosso, Bin Li, Philippe Cudré-Mauroux:
NodeSketch: Highly-Efficient Graph Embeddings via Recursive Sketching. 1162-1172 - Chengrun Yang, Yuji Akimoto, Dae Won Kim, Madeleine Udell:
OBOE: Collaborative Filtering for AutoML Model Selection. 1173-1183 - Li He, Long Xia, Wei Zeng, Zhi-Ming Ma, Yihong Zhao, Dawei Yin:
Off-policy Learning for Multiple Loggers. 1184-1193 - Yu-Chia Chen, Avleen S. Bijral, Juan Lavista Ferres:
On Dynamic Network Models and Application to Causal Impact. 1194-1204 - Yipeng Zhang, Yuchen Li, Zhifeng Bao, Songsong Mo, Ping Zhang:
Optimizing Impression Counts for Outdoor Advertising. 1205-1215 - Mohammadreza Esfandiari, Dong Wei, Sihem Amer-Yahia, Senjuti Basu Roy:
Optimizing Peer Learning in Online Groups with Affinities. 1216-1226 - Yuandong Wang, Hongzhi Yin, Hongxu Chen, Tianyu Wo, Jie Xu, Kai Zheng:
Origin-Destination Matrix Prediction via Graph Convolution: a New Perspective of Passenger Demand Modeling. 1227-1235 - Lucas Maystre, Victor Kristof, Matthias Grossglauser:
Pairwise Comparisons with Flexible Time-Dynamics. 1236-1246 - Ari Kobren, Barna Saha, Andrew McCallum:
Paper Matching with Local Fairness Constraints. 1247-1257 - Sanjoy Dey, Ping Zhang, Daby Sow, Kenney Ng:
PerDREP: Personalized Drug Effectiveness Prediction from Longitudinal Observational Data. 1258-1268 - Srijan Kumar, Xikun Zhang, Jure Leskovec:
Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks. 1269-1278 - Jia Li, Zhichao Han, Hong Cheng, Jiao Su, Pengyun Wang, Jianfeng Zhang, Lujia Pan:
Predicting Path Failure In Time-Evolving Graphs. 1279-1289 - Hua Wei, Chacha Chen, Guanjie Zheng, Kan Wu, Vikash V. Gayah, Kai Xu, Zhenhui Li:
PressLight: Learning Max Pressure Control to Coordinate Traffic Signals in Arterial Network. 1290-1298 - Yi Li, Wei Xu:
PrivPy: General and Scalable Privacy-Preserving Data Mining. 1299-1307 - Hongchang Gao, Jian Pei, Heng Huang:
ProGAN: Network Embedding via Proximity Generative Adversarial Network. 1308-1316 - Francois Belletti, Minmin Chen, Ed H. Chi:
Quantifying Long Range Dependence in Language and User Behavior to improve RNNs. 1317-1327 - Yu Yin, Qi Liu, Zhenya Huang, Enhong Chen, Wei Tong, Shijin Wang, Yu Su:
QuesNet: A Unified Representation for Heterogeneous Test Questions. 1328-1336 - Souhaib Ben Taieb, Bonsoo Koo:
Regularized Regression for Hierarchical Forecasting Without Unbiasedness Conditions. 1337-1347 - Shimin Di, Yanyan Shen, Lei Chen:
Relation Extraction via Domain-aware Transfer Learning. 1348-1357 - Yukuo Cen, Xu Zou, Jianwei Zhang, Hongxia Yang, Jingren Zhou, Jie Tang:
Representation Learning for Attributed Multiplex Heterogeneous Network. 1358-1368 - Fengyi Tang, Cao Xiao, Fei Wang, Jiayu Zhou, Li-Wei H. Lehman:
Retaining Privileged Information for Multi-Task Learning. 1369-1377 - Parikshit Ram, Kaushik Sinha:
Revisiting kd-tree for Nearest Neighbor Search. 1378-1388 - Jie Zhao, Ziyu Guan, Huan Sun:
Riker: Mining Rich Keyword Representations for Interpretable Product Question Answering. 1389-1398 - Dingyuan Zhu, Ziwei Zhang, Peng Cui, Wenwu Zhu:
Robust Graph Convolutional Networks Against Adversarial Attacks. 1399-1407 - Yaqiang Yao, Jie Cao, Huanhuan Chen:
Robust Task Grouping with Representative Tasks for Clustered Multi-Task Learning. 1408-1417 - Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia, Charu C. Aggarwal:
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding. 1418-1428 - Yuan Yin, Zhewei Wei:
Scalable Graph Embeddings via Sparse Transpose Proximities. 1429-1437 - Nicholas Monath, Ari Kobren, Akshay Krishnamurthy, Michael R. Glass, Andrew McCallum:
Scalable Hierarchical Clustering with Tree Grafting. 1438-1448 - Edouard Fouché, Junpei Komiyama, Klemens Böhm:
Scaling Multi-Armed Bandit Algorithms. 1449-1459 - Parameswaran Raman, Sriram Srinivasan, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan:
Scaling Multinomial Logistic Regression via Hybrid Parallelism. 1460-1470 - Luobao Zou, Zhiwei Zhuang, Yin Cheng, Xuechun Wang, Weidong Zhang:
Separated Trust Regions Policy Optimization Method. 1471-1479 - Min-hwan Oh, Garud Iyengar:
Sequential Anomaly Detection using Inverse Reinforcement Learning. 1480-1490 - Haoji Hu, Xiangnan He:
Sets2Sets: Learning from Sequential Sets with Neural Networks. 1491-1499 - Madelon Hulsebos, Kevin Zeng Hu, Michiel A. Bakker, Emanuel Zgraggen, Arvind Satyanarayan, Tim Kraska, Çagatay Demiralp, César A. Hidalgo:
Sherlock: A Deep Learning Approach to Semantic Data Type Detection. 1500-1508 - Rafael Savvides, Andreas Henelius, Emilia Oikarinen, Kai Puolamäki:
Significance of Patterns in Data Visualisations. 1509-1517 - Xin Wang, Wenwu Zhu, Chenghao Liu:
Social Recommendation with Optimal Limited Attention. 1518-1527 - Leonardo Pellegrina, Matteo Riondato, Fabio Vandin:
SPuManTE: Significant Pattern Mining with Unconditional Testing. 1528-1538 - Saurabh Verma, Zhi-Li Zhang:
Stability and Generalization of Graph Convolutional Neural Networks. 1539-1548 - Hongzhi Shi, Chao Zhang, Quanming Yao, Yong Li, Funing Sun, Depeng Jin:
State-Sharing Sparse Hidden Markov Models for Personalized Sequences. 1549-1559 - Prathamesh Deshpande, Sunita Sarawagi:
Streaming Adaptation of Deep Forecasting Models using Adaptive Recurrent Units. 1560-1568 - Lei Guo, Hongzhi Yin, Qinyong Wang, Tong Chen, Alexander Zhou, Nguyen Quoc Viet Hung:
Streaming Session-based Recommendation. 1569-1577 - Zhen Wang, Xiang Yue, Soheil Moosavinasab, Yungui Huang, Simon M. Lin, Huan Sun:
SurfCon: Synonym Discovery on Privacy-Aware Clinical Data. 1578-1586 - Shuyang Yu, Bin Gu, Kunpeng Ning, Haiyan Chen, Jian Pei, Heng Huang:
Tackle Balancing Constraint for Incremental Semi-Supervised Support Vector Learning. 1587-1595 - Pei Yang, Qi Tan, Hanghang Tong, Jingrui He:
Task-Adversarial Co-Generative Nets. 1596-1604 - Romain Warlop, Jérémie Mary, Mike Gartrell:
Tensorized Determinantal Point Processes for Recommendation. 1605-1615 - Yuan Deng, Sébastien Lahaie:
Testing Dynamic Incentive Compatibility in Display Ad Auctions. 1616-1624 - Ying Sun, Fuzhen Zhuang, Hengshu Zhu, Xin Song, Qing He, Hui Xiong:
The Impact of Person-Organization Fit on Talent Management: A Structure-Aware Convolutional Neural Network Approach. 1625-1633 - Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang:
The Role of: A Novel Scientific Knowledge Graph Representation and Construction Model. 1634-1642 - Boyang Li, Yurong Cheng, Ye Yuan, Guoren Wang, Lei Chen:
Three-Dimensional Stable Matching Problem for Spatial Crowdsourcing Platforms. 1643-1653 - Stefano Giovanni Rizzo, Giovanna Vantini, Sanjay Chawla:
Time Critic Policy Gradient Methods for Traffic Signal Control in Complex and Congested Scenarios. 1654-1664 - Xiaowei Jia, Sheng Li, Handong Zhao, Sungchul Kim, Vipin Kumar:
Towards Robust and Discriminative Sequential Data Learning: When and How to Perform Adversarial Training? 1665-1673 - Abdulah Fawaz, Paul Klein, Sebastien Piat, Simone Severini, Peter Mountney:
Training and Meta-Training Binary Neural Networks with Quantum Computing. 1674-1681 - Daheng Wang, Tianwen Jiang, Nitesh V. Chawla, Meng Jiang:
TUBE: Embedding Behavior Outcomes for Predicting Success. 1682-1690 - Chengxi Zang, Peng Cui, Chaoming Song, Wenwu Zhu, Fei Wang:
Uncovering Pattern Formation of Information Flow. 1691-1699 - Yunchao Zhang, Yanjie Fu, Pengyang Wang, Xiaolin Li, Yu Zheng:
Unifying Inter-region Autocorrelation and Intra-region Structures for Spatial Embedding via Collective Adversarial Learning. 1700-1708 - Junheng Hao, Muhao Chen, Wenchao Yu, Yizhou Sun, Wei Wang:
Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts. 1709-1719 - Zheyi Pan, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, Junbo Zhang:
Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning. 1720-1730
Applied Data Science Track Papers
- Lucas Bernardi, Themistoklis Mavridis, Pablo Estevez:
150 Successful Machine Learning Models: 6 Lessons Learned at Booking.com. 1743-1751 - Jingbo Zhou, Shan Gou, Renjun Hu, Dongxiang Zhang, Jin Xu, Airong Jiang, Ying Li, Hui Xiong:
A Collaborative Learning Framework to Tag Refinement for Points of Interest. 1752-1761 - Lei Chen, Xialiang Tong, Mingxuan Yuan, Jia Zeng, Lei Chen:
A Data-Driven Approach for Multi-level Packing Problems in Manufacturing Industry. 1762-1770 - Fred X. Han, Di Niu, Haolan Chen, Kunfeng Lai, Yancheng He, Yu Xu:
A Deep Generative Approach to Search Extrapolation and Recommendation. 1771-1779 - Xiaocheng Tang, Zhiwei (Tony) Qin, Fan Zhang, Zhaodong Wang, Zhe Xu, Yintai Ma, Hongtu Zhu, Jieping Ye:
A Deep Value-network Based Approach for Multi-Driver Order Dispatching. 1780-1790 - Ang Li, Ola Spyra, Sagi Perel, Valentin Dalibard, Max Jaderberg, Chenjie Gu, David Budden, Tim Harley, Pramod Gupta:
A Generalized Framework for Population Based Training. 1791-1799 - Prithwish Chakraborty, Faisal Farooq:
A Robust Framework for Accelerated Outcome-driven Risk Factor Identification from EHR. 1800-1808 - Peng Tian, Yuan Guo, Jayashree Kalpathy-Cramer, Susan Ostmo, John Peter Campbell, Michael F. Chiang, Jennifer G. Dy, Deniz Erdogmus, Stratis Ioannidis:
A Severity Score for Retinopathy of Prematurity. 1809-1819 - Kui Zhao, Junhao Hua, Ling Yan, Qi Zhang, Huan Xu, Cheng Yang:
A Unified Framework for Marketing Budget Allocation. 1820-1830 - Bang Liu, Weidong Guo, Di Niu, Chaoyue Wang, Shunnan Xu, Jinghong Lin, Kunfeng Lai, Yu Xu:
A User-Centered Concept Mining System for Query and Document Understanding at Tencent. 1831-1841 - Zhipeng Luo, Jianqiang Huang, Ke Hu, Xue Li, Peng Zhang:
AccuAir: Winning Solution to Air Quality Prediction for KDD Cup 2018. 1842-1850 - Tom Decroos, Lotte Bransen, Jan Van Haaren, Jesse Davis:
Actions Speak Louder than Goals: Valuing Player Actions in Soccer. 1851-1861 - H. M. Sajjad Hossain, Nirmalya Roy:
Active Deep Learning for Activity Recognition with Context Aware Annotator Selection. 1862-1870 - Xiao Hui Tai, Kyle Soska, Nicolas Christin:
Adversarial Matching of Dark Net Market Vendor Accounts. 1871-1880 - Xiao Yang, Daren Sun, Ruiwei Zhu, Tao Deng, Zhi Guo, Zongyao Ding, Shouke Qin, Yanfeng Zhu:
AiAds: Automated and Intelligent Advertising System for Sponsored Search. 1881-1890 - Xiaoli Tang, Tengyun Wang, Haizhi Yang, Hengjie Song:
AKUPM: Attention-Enhanced Knowledge-Aware User Preference Model for Recommendation. 1891-1899 - Jingyuan Wang, Yang Zhang, Ke Tang, Junjie Wu, Zhang Xiong:
AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks. 1900-1908 - Yichen Shen, Maxime Voisin, Alireza Aliamiri, Anand Avati, Awni Y. Hannun, Andrew Y. Ng:
Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning. 1909-1916 - Jagdish Ramakrishnan, Elham Shaabani, Chao Li, Mátyás A. Sustik:
Anomaly Detection for an E-commerce Pricing System. 1917-1926 - Malay Haldar, Mustafa Abdool, Prashant Ramanathan, Tao Xu, Shulin Yang, Huizhong Duan, Qing Zhang, Nick Barrow-Williams, Bradley C. Turnbull, Brendan M. Collins, Thomas Legrand:
Applying Deep Learning to Airbnb Search. 1927-1935 - Yuanfei Luo, Mengshuo Wang, Hao Zhou, Quanming Yao, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang:
AutoCross: Automatic Feature Crossing for Tabular Data in Real-World Applications. 1936-1945 - Haifeng Jin, Qingquan Song, Xia Hu:
Auto-Keras: An Efficient Neural Architecture Search System. 1946-1956 - Chunyi Liu, Peng Wang, Jiang Xu, Zang Li, Jieping Ye:
Automatic Dialogue Summary Generation for Customer Service. 1957-1965 - Xun Yang, Yasong Li, Hao Wang, Di Wu, Qing Tan, Jian Xu, Kun Gai:
Bid Optimization by Multivariable Control in Display Advertising. 1966-1974 - Lisa Singh, Laila Wahedi, Yanchen Wang, Yifang Wei, Christo Kirov, Susan Martin, Katharine M. Donato, Yaguang Liu, Kornraphop Kawintiranon:
Blending Noisy Social Media Signals with Traditional Movement Variables to Predict Forced Migration. 1975-1983 - Long Guo, Lifeng Hua, Rongfei Jia, Binqiang Zhao, Xiaobo Wang, Bin Cui:
Buying or Browsing?: Predicting Real-time Purchasing Intent using Attention-based Deep Network with Multiple Behavior. 1984-1992 - Michal Aharon, Oren Somekh, Avi Shahar, Assaf Singer, Baruch Trayvas, Hadas Vogel, Dobri Dobrev:
Carousel Ads Optimization in Yahoo Gemini Native. 1993-2001 - Seiya Tokui, Ryosuke Okuta, Takuya Akiba, Yusuke Niitani, Toru Ogawa, Shunta Saito, Shuji Suzuki, Kota Uenishi, Brian Vogel, Hiroyuki Yamazaki Vincent:
Chainer: A Deep Learning Framework for Accelerating the Research Cycle. 2002-2011 - Zenghua Xia, Chang Liu, Neil Zhenqiang Gong, Qi Li, Yong Cui, Dawn Song:
Characterizing and Detecting Malicious Accounts in Privacy-Centric Mobile Social Networks: A Case Study. 2012-2022 - Yozen Liu, Xiaolin Shi, Lucas Pierce, Xiang Ren:
Characterizing and Forecasting User Engagement with In-App Action Graph: A Case Study of Snapchat. 2023-2031 - Pan Li, Zhen Qin, Xuanhui Wang, Donald Metzler:
Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search. 2032-2040 - Chen Zhe, Aixin Sun, Xiaokui Xiao:
Community Detection on Large Complex Attribute Network. 2041-2049 - Ari Kobren, Pablo Barrio, Oksana Yakhnenko, Johann Hibschman, Ian Langmore:
Constructing High Precision Knowledge Bases with Subjective and Factual Attributes. 2050-2058 - Jan-Philipp Schulze, Artur Mrowca, Elizabeth Ren, Hans-Andrea Loeliger, Konstantin Böttinger:
Context by Proxy: Identifying Contextual Anomalies Using an Output Proxy. 2059-2068 - Shunsuke Kitada, Hitoshi Iyatomi, Yoshifumi Seki:
Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creatives. 2069-2077 - Wentao Ouyang, Xiuwu Zhang, Li Li, Heng Zou, Xin Xing, Zhaojie Liu, Yanlong Du:
Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction. 2078-2086 - Bin Wang, Jie Lu, Zheng Yan, Huaishao Luo, Tianrui Li, Yu Zheng, Guangquan Zhang:
Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting. 2087-2095 - Anthony Sicilia, Konstantinos Pelechrinis, Kirk Goldsberry:
DeepHoops: Evaluating Micro-Actions in Basketball Using Deep Feature Representations of Spatio-Temporal Data. 2096-2104 - Stephen Lee, Srinivasan Iyengar, Menghong Feng, Prashant J. Shenoy, Subhransu Maji:
DeepRoof: A Data-driven Approach For Solar Potential Estimation Using Rooftop Imagery. 2105-2113 - Renhe Jiang, Xuan Song, Dou Huang, Xiaoya Song, Tianqi Xia, Zekun Cai, Zhaonan Wang, Kyoung-Sook Kim, Ryosuke Shibasaki:
DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big Events. 2114-2122 - Shahroz Tariq, Sangyup Lee, Youjin Shin, Myeong Shin Lee, Okchul Jung, Daewon Chung, Simon S. Woo:
Detecting Anomalies in Space using Multivariate Convolutional LSTM with Mixtures of Probabilistic PCA. 2123-2133 - Anil R. Yelundur, Vineet Chaoji, Bamdev Mishra:
Detection of Review Abuse via Semi-Supervised Binary Multi-Target Tensor Decomposition. 2134-2144 - Richard Chen, Filip Jankovic, Nikki Marinsek, Luca Foschini, Lampros Kourtis, Alessio Signorini, Melissa Pugh, Jie Shen, Roy Yaari, Vera Maljkovic, Marc Sunga, Han Hee Song, Hyun Joon Jung, Belle L. Tseng, Andrew Trister:
Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams. 2145-2155 - Aleksander Fabijan, Jayant Gupchup, Somit Gupta, Jeff Omhover, Wen Qin, Lukas Vermeer, Pavel A. Dmitriev:
Diagnosing Sample Ratio Mismatch in Online Controlled Experiments: A Taxonomy and Rules of Thumb for Practitioners. 2156-2164 - Chuan Qin, Hengshu Zhu, Chen Zhu, Tong Xu, Fuzhen Zhuang, Chao Ma, Jingshuai Zhang, Hui Xiong:
DuerQuiz: A Personalized Question Recommender System for Intelligent Job Interview. 2165-2173 - Naman Shukla, Arinbjörn Kolbeinsson, Ken Otwell, Lavanya Marla, Kartik Yellepeddi:
Dynamic Pricing for Airline Ancillaries with Customer Context. 2174-2182 - Dmitrii Babaev, Maxim Savchenko, Alexander Tuzhilin, Dmitrii Umerenkov:
E.T.-RNN: Applying Deep Learning to Credit Loan Applications. 2183-2190 - Kiri L. Wagstaff, Gary Doran, Ashley Davies, Saadat Anwar, Srija Chakraborty, Marissa Cameron, Ingrid Daubar, Cynthia A. Phillips:
Enabling Onboard Detection of Events of Scientific Interest for the Europa Clipper Spacecraft. 2191-2201 - Laurence Yang, Michael A. Saunders, Jean-Christophe Lachance, Bernhard O. Palsson, José Bento:
Estimating Cellular Goals from High-Dimensional Biological Data. 2202-2211 - Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H. Chi, Cristos Goodrow:
Fairness in Recommendation Ranking through Pairwise Comparisons. 2212-2220 - Sahin Cem Geyik, Stuart Ambler, Krishnaram Kenthapadi:
Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search. 2221-2231 - Yaochen Hu, Di Niu, Jianming Yang, Shengping Zhou:
FDML: A Collaborative Machine Learning Framework for Distributed Features. 2232-2240 - Ye Tu, Chun Lo, Yiping Yuan, Shaunak Chatterjee:
Feedback Shaping: A Modeling Approach to Nurture Content Creation. 2241-2250 - Stephanie deWet, Jiafan Ou:
Finding Users Who Act Alike: Transfer Learning for Expanding Advertiser Audiences. 2251-2259 - Doyen Sahoo, Hao Wang, Shu Ke, Xiongwei Wu, Hung Le, Palakorn Achananuparp, Ee-Peng Lim, Steven C. H. Hoi:
FoodAI: Food Image Recognition via Deep Learning for Smart Food Logging. 2260-2268 - J. Weston Hughes, Keng-hao Chang, Ruofei Zhang:
Generating Better Search Engine Text Advertisements with Deep Reinforcement Learning. 2269-2277 - Yuhui Zheng, Linchuan Xu, Taichi Kiwaki, Jing Wang, Hiroshi Murata, Ryo Asaoka, Kenji Yamanishi:
Glaucoma Progression Prediction Using Retinal Thickness via Latent Space Linear Regression. 2278-2286 - Mia Xu Chen, Benjamin N. Lee, Gagan Bansal, Yuan Cao, Shuyuan Zhang, Justin Lu, Jackie Tsay, Yinan Wang, Andrew M. Dai, Zhifeng Chen, Timothy Sohn, Yonghui Wu:
Gmail Smart Compose: Real-Time Assisted Writing. 2287-2295 - Neha Arora, James Cook, Ravi Kumar, Ivan Kuznetsov, Yechen Li, Huai-Jen Liang, Andrew Miller, Andrew Tomkins, Iveel Tsogsuren, Yi Wang:
Hard to Park?: Estimating Parking Difficulty at Scale. 2296-2304 - Shanshan Zhang, Lihong He, Eduard C. Dragut, Slobodan Vucetic:
How to Invest my Time: Lessons from Human-in-the-Loop Entity Extraction. 2305-2313 - Hao Liu, Yongxin Tong, Panpan Zhang, Xinjiang Lu, Jianguo Duan, Hui Xiong:
Hydra: A Personalized and Context-Aware Multi-Modal Transportation Recommendation System. 2314-2324 - Jessica Hwang, Paulo Orenstein, Judah Cohen, Karl Pfeiffer, Lester Mackey:
Improving Subseasonal Forecasting in the Western U.S. with Machine Learning. 2325-2335 - Xichen Ding, Jie Tang, Tracy Xiao Liu, Cheng Xu, Yaping Zhang, Feng Shi, Qixia Jiang, Dan Shen:
Infer Implicit Contexts in Real-time Online-to-Offline Recommendation. 2336-2346 - Jun Zhao, Zhou Zhou, Ziyu Guan, Wei Zhao, Wei Ning, Guang Qiu, Xiaofei He:
IntentGC: A Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation. 2347-2357 - Rupesh Gupta, Guangde Chen, Shipeng Yu:
Internal Promotion Optimization. 2358-2366 - John Lu, Sumati Sridhar, Ritika Pandey, Mohammad Al Hasan, George O. Mohler:
Investigate Transitions into Drug Addiction through Text Mining of Reddit Data. 2367-2375 - Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu:
Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction. 2376-2384 - Dipendra Jha, Logan T. Ward, Zijiang Yang, Christopher Wolverton, Ian T. Foster, Wei-keng Liao, Alok N. Choudhary, Ankit Agrawal:
IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery. 2385-2393 - Seong Jae Hwang, Joonseok Lee, Balakrishnan Varadarajan, Ariel Gordon, Zheng Xu, Apostol Natsev:
Large-Scale Training Framework for Video Annotation. 2394-2402 - Xiaoyang Ma, Lan Zhang, Lan Xu, Zhicheng Liu, Ge Chen, Zhili Xiao, Yang Wang, Zhengtao Wu:
Large-scale User Visits Understanding and Forecasting with Deep Spatial-Temporal Tensor Factorization Framework. 2403-2411 - Andrew Zhai, Hao-Yu Wu, Eric Tzeng, Dong Huk Park, Charles Rosenberg:
Learning a Unified Embedding for Visual Search at Pinterest. 2412-2420 - Sungkyu Park, Cheng-Te Li, Sungwon Han, Cheng Hsu, Sang Won Lee, Meeyoung Cha:
Learning Sleep Quality from Daily Logs. 2421-2429 - Jackson A. Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, Milind Tambe:
Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data. 2430-2438 - Yangli-ao Geng, Qingyong Li, Tianyang Lin, Lei Jiang, Liangtao Xu, Dong Zheng, Wen Yao, Weitao Lyu, Yijun Zhang:
LightNet: A Dual Spatiotemporal Encoder Network Model for Lightning Prediction. 2439-2447 - Zeeshan Ahmed, Saeed Amizadeh, Mikhail Bilenko, Rogan Carr, Wei-Sheng Chin, Yael Dekel, Xavier Dupré, Vadim Eksarevskiy, Senja Filipi, Tom Finley, Abhishek Goswami, Monte Hoover, Scott Inglis, Matteo Interlandi, Najeeb Kazmi, Gleb Krivosheev, Pete Luferenko, Ivan Matantsev, Sergiy Matusevych, Shahab Moradi, Gani Nazirov, Justin Ormont, Gal Oshri, Artidoro Pagnoni, Jignesh Parmar, Prabhat Roy, Mohammad Zeeshan Siddiqui, Markus Weimer, Shauheen Zahirazami, Yiwen Zhu:
Machine Learning at Microsoft with ML.NET. 2448-2458 - Megha Srivastava, Hoda Heidari, Andreas Krause:
Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning. 2459-2468 - Junting Ye, Steven Skiena:
MediaRank: Computational Ranking of Online News Sources. 2469-2477 - Shaohua Fan, Junxiong Zhu, Xiaotian Han, Chuan Shi, Linmei Hu, Biyu Ma, Yongliang Li:
Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation. 2478-2486 - Xi Sheryl Zhang, Fengyi Tang, Hiroko H. Dodge, Jiayu Zhou, Fei Wang:
MetaPred: Meta-Learning for Clinical Risk Prediction with Limited Patient Electronic Health Records. 2487-2495 - Miao Fan, Jiacheng Guo, Shuai Zhu, Shuo Miao, Mingming Sun, Ping Li:
MOBIUS: Towards the Next Generation of Query-Ad Matching in Baidu's Sponsored Search. 2509-2517 - Yina Tang, Fedor Borisyuk, Siddarth Malreddy, Yixuan Li, Yiqun Liu, Sergey Kirshner:
MSURU: Large Scale E-commerce Image Classification with Weakly Supervised Search Data. 2518-2526 - Chenyou Fan, Yuze Zhang, Yi Pan, Xiaoyue Li, Chi Zhang, Rong Yuan, Di Wu, Wensheng Wang, Jian Pei, Heng Huang:
Multi-Horizon Time Series Forecasting with Temporal Attention Learning. 2527-2535 - Jianrong Tao, Jianshi Lin, Shize Zhang, Sha Zhao, Runze Wu, Changjie Fan, Peng Cui:
MVAN: Multi-view Attention Networks for Real Money Trading Detection in Online Games. 2536-2546 - Bhanu Pratap Singh Rawat, Fei Li, Hong Yu:
Naranjo Question Answering using End-to-End Multi-task Learning Model. 2547-2555 - Yumin Liu, Junxiang Chen, Auroop R. Ganguly, Jennifer G. Dy:
Nonparametric Mixture of Sparse Regressions on Spatio-Temporal Data - An Application to Climate Prediction. 2556-2564 - Amol Kapoor, Hunter Larco, Raimondas Kiveris:
Nostalgin: Extracting 3D City Models from Historical Image Data. 2565-2575 - Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang, Xing Xie:
NPA: Neural News Recommendation with Personalized Attention. 2576-2584 - Fanjin Zhang, Xiao Liu, Jie Tang, Yuxiao Dong, Peiran Yao, Jie Zhang, Xiaotao Gu, Yan Wang, Bin Shao, Rui Li, Kuansan Wang:
OAG: Toward Linking Large-scale Heterogeneous Entity Graphs. 2585-2595 - Yue Weng, Huaixiu Zheng, Franziska Bell, Gökhan Tür:
OCC: A Smart Reply System for Efficient In-App Communications. 2596-2603 - Chin-Chia Michael Yeh, Yan Zhu, Hoang Anh Dau, Amirali Darvishzadeh, Mikhail Noskov, Eamonn J. Keogh:
Online Amnestic DTW to allow Real-Time Golden Batch Monitoring. 2604-2612 - Chao Huang, Xian Wu, Xuchao Zhang, Chuxu Zhang, Jiashu Zhao, Dawei Yin, Nitesh V. Chawla:
Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics. 2613-2622 - Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, Masanori Koyama:
Optuna: A Next-generation Hyperparameter Optimization Framework. 2623-2631 - Wei Zhao, Boxuan Zhang, Beidou Wang, Ziyu Guan, Wanxian Guan, Guang Qiu, Wei Ning, Jiming Chen, Hongmin Liu:
Personalized Attraction Enhanced Sponsored Search with Multi-task Learning. 2632-2642 - Mathias Kraus, Stefan Feuerriegel:
Personalized Purchase Prediction of Market Baskets with Wasserstein-Based Sequence Matching. 2643-2652 - Jinfeng Zhuang, Yu Liu:
PinText: A Multitask Text Embedding System in Pinterest. 2653-2661 - Wen Chen, Pipei Huang, Jiaming Xu, Xin Guo, Cheng Guo, Fei Sun, Chao Li, Andreas Pfadler, Huan Zhao, Binqiang Zhao:
POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion. 2662-2670 - Qi Pi, Weijie Bian, Guorui Zhou, Xiaoqiang Zhu, Kun Gai:
Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction. 2671-2679 - Vadim Lebedev, Vladimir Ivashkin, Irina Rudenko, Alexander Ganshin, Alexander Molchanov, Sergey Ovcharenko, Ruslan Grokhovetskiy, Ivan Bushmarinov, Dmitry Solomentsev:
Precipitation Nowcasting with Satellite Imagery. 2680-2688 - Junwei Pan, Yizhi Mao, Alfonso Lobos Ruiz, Yu Sun, Aaron Flores:
Predicting Different Types of Conversions with Multi-Task Learning in Online Advertising. 2689-2697 - Evan Sheehan, Chenlin Meng, Matthew Tan, Burak Uzkent, Neal Jean, Marshall Burke, David B. Lobell, Stefano Ermon:
Predicting Economic Development using Geolocated Wikipedia Articles. 2698-2706 - Takahiro Yabe, Kota Tsubouchi, Toru Shimizu, Yoshihide Sekimoto, Satish V. Ukkusuri:
Predicting Evacuation Decisions using Representations of Individuals' Pre-Disaster Web Search Behavior. 2707-2717 - Ehimwenma Nosakhare, Rosalind W. Picard:
Probabilistic Latent Variable Modeling for Assessing Behavioral Influences on Well-Being. 2718-2726 - Alexey Svyatkovskiy, Ying Zhao, Shengyu Fu, Neel Sundaresan:
Pythia: AI-assisted Code Completion System. 2727-2735 - Shiwen Zhao, Brandt Westing, Shawn Scully, Heri Nieto, Roman Holenstein, Minwoo Jeong, Krishna Sridhar, Brandon Newendorp, Mike Bastian, Sethu Raman, Tim Paek, Kevin Lynch, Carlos Guestrin:
Raise to Speak: An Accurate, Low-power Detector for Activating Voice Assistants on Smartwatches. 2736-2744 - David Rolnick, Kevin Aydin, Jean Pouget-Abadie, Shahab Kamali, Vahab S. Mirrokni, Amir Najmi:
Randomized Experimental Design via Geographic Clustering. 2745-2753 - Peng Jiang, Yingrui Yang, Gann Bierner, Fengjie Alex Li, Ruhan Wang, Azadeh Moghtaderi:
Ranking in Genealogy: Search Results Fusion at Ancestry. 2754-2764 - Yudan Liu, Kaikai Ge, Xu Zhang, Leyu Lin:
Real-time Attention Based Look-alike Model for Recommender System. 2765-2773 - Mateusz Fedoryszak, Brent Frederick, Vijay Rajaram, Changtao Zhong:
Real-time Event Detection on Social Data Streams. 2774-2782 - Keiichi Ochiai, Kohei Senkawa, Naoki Yamamoto, Yuya Tanaka, Yusuke Fukazawa:
Real-time On-Device Troubleshooting Recommendation for Smartphones. 2783-2791 - Tadashi Okoshi, Kota Tsubouchi, Hideyuki Tokuda:
Real-World Product Deployment of Adaptive Push Notification Scheduling on Smartphones. 2792-2800 - Nicolas Grislain, Nicolas Perrin, Antoine Thabault:
Recurrent Neural Networks for Stochastic Control in Real-Time Bidding. 2801-2809 - Lixin Zou, Long Xia, Zhuoye Ding, Jiaxing Song, Weidong Liu, Dawei Yin:
Reinforcement Learning to Optimize Long-term User Engagement in Recommender Systems. 2810-2818 - Achir Kalra, Chong Wang, Cristian Borcea, Yi Chen:
Reserve Price Failure Rate Prediction with Header Bidding in Display Advertising. 2819-2827 - Ya Su, Youjian Zhao, Chenhao Niu, Rong Liu, Wei Sun, Dan Pei:
Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network. 2828-2837 - Ming Lin, Xiaomin Song, Qi Qian, Hao Li, Liang Sun, Shenghuo Zhu, Rong Jin:
Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement. 2838-2847 - Zhibin Li, Jian Zhang, Qiang Wu, Yongshun Gong, Jinfeng Yi, Christina Kirsch:
Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points. 2848-2856 - Thien Q. Tran, Jun Sakuma:
Seasonal-adjustment Based Feature Selection Method for Predicting Epidemic with Large-scale Search Engine Logs. 2857-2866 - Ari Biswas, Thai T. Pham, Michael Vogelsong, Benjamin Snyder, Houssam Nassif:
Seeker: Real-Time Interactive Search. 2867-2875 - Priyanka Nigam, Yiwei Song, Vijai Mohan, Vihan Lakshman, Weitian Allen Ding, Ankit Shingavi, Choon Hui Teo, Hao Gu, Bing Yin:
Semantic Product Search. 2876-2885 - Dimitris Spathis, Sandra Servia Rodríguez, Katayoun Farrahi, Cecilia Mascolo, Jason Rentfrow:
Sequence Multi-task Learning to Forecast Mental Wellbeing from Sparse Self-reported Data. 2886-2894 - Zhengxiao Du, Xiaowei Wang, Hongxia Yang, Jingren Zhou, Jie Tang:
Sequential Scenario-Specific Meta Learner for Online Recommendation. 2895-2904 - Sobhan Moosavi, Mohammad Hossein Samavatian, Arnab Nandi, Srinivasan Parthasarathy, Rajiv Ramnath:
Short and Long-term Pattern Discovery Over Large-Scale Geo-Spatiotemporal Data. 2905-2913 - Drew Dimmery, Eytan Bakshy, Jasjeet S. Sekhon:
Shrinkage Estimators in Online Experiments. 2914-2922 - Di Jin, Mark Heimann, Tara Safavi, Mengdi Wang, Wei Lee, Lindsay Snider, Danai Koutra:
Smart Roles: Inferring Professional Roles in Email Networks. 2923-2933 - Abhilash Reddy Chenreddy, Parshan Pakiman, Selvaprabu Nadarajah, Ranganathan Chandrasekaran, Rick Abens:
SMOILE: A Shopper Marketing Optimization and Inverse Learning Engine. 2934-2942 - Xiao Yan, Jaewon Yang, Mikhail Obukhov, Lin Zhu, Joey Bai, Shiqi Wu, Qi He:
Social Skill Validation at LinkedIn. 2943-2951 - Farhan Asif Chowdhury, Satomi Suzuki, Abdullah Mueen:
Structured Noise Detection: Application on Well Test Pressure Derivative Data. 2952-2960 - Eitam Sheetrit, Nir Nissim, Denis Klimov, Yuval Shahar:
Temporal Probabilistic Profiles for Sepsis Prediction in the ICU. 2961-2969 - Rama Kumar Pasumarthi, Sebastian Bruch, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork, Jan Pfeifer, Nadav Golbandi, Rohan Anil, Stephan Wolf:
TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank. 2970-2978 - Christian Schön, Jens Dittrich, Richard Müller:
The Error is the Feature: How to Forecast Lightning using a Model Prediction Error. 2979-2988 - Xuan Yin, Liangjie Hong:
The Identification and Estimation of Direct and Indirect Effects in A/B Tests through Causal Mediation Analysis. 2989-2999 - Junting Ye, Steven Skiena:
The Secret Lives of Names?: Name Embeddings from Social Media. 3000-3008 - Hansheng Ren, Bixiong Xu, Yujing Wang, Chao Yi, Congrui Huang, Xiaoyu Kou, Tony Xing, Mao Yang, Jie Tong, Qi Zhang:
Time-Series Anomaly Detection Service at Microsoft. 3009-3017 - Xiao Zhou, Cecilia Mascolo, Zhongxiang Zhao:
Topic-Enhanced Memory Networks for Personalised Point-of-Interest Recommendation. 3018-3028 - Shobha Venkataraman, Jia Wang:
Towards Identifying Impacted Users in Cellular Services. 3029-3039 - Qibin Chen, Junyang Lin, Yichang Zhang, Hongxia Yang, Jingren Zhou, Jie Tang:
Towards Knowledge-Based Personalized Product Description Generation in E-commerce. 3040-3050 - Kevin Fauvel, Véronique Masson, Élisa Fromont, Philippe Faverdin, Alexandre Termier:
Towards Sustainable Dairy Management - A Machine Learning Enhanced Method for Estrus Detection. 3051-3059 - Zheyi Pan, Jie Bao, Weinan Zhang, Yong Yu, Yu Zheng:
TrajGuard: A Comprehensive Trajectory Copyright Protection Scheme. 3060-3070 - Yasuhisa Suzuki, Wemer M. Wee, Itaru Nishioka:
TV Advertisement Scheduling by Learning Expert Intentions. 3071-3081 - Tom Sühr, Asia J. Biega, Meike Zehlike, Krishna P. Gummadi, Abhijnan Chakraborty:
Two-Sided Fairness for Repeated Matchings in Two-Sided Markets: A Case Study of a Ride-Hailing Platform. 3082-3092 - Yunfei Lu, Linyun Yu, Peng Cui, Chengxi Zang, Renzhe Xu, Yihao Liu, Lei Li, Wenwu Zhu:
Uncovering the Co-driven Mechanism of Social and Content Links in User Churn Phenomena. 3093-3101 - Yichao Zhou, Shaunak Mishra, Jelena Gligorijevic, Tarun Bhatia, Narayan Bhamidipati:
Understanding Consumer Journey using Attention based Recurrent Neural Networks. 3102-3111 - Hao Jiang, Aakash Sabharwal, Adam Henderson, Diane Hu, Liangjie Hong:
Understanding the Role of Style in E-commerce Shopping. 3112-3120 - Wei-Hung Weng, Yu-An Chung, Peter Szolovits:
Unsupervised Clinical Language Translation. 3121-3131 - Yuxuan Liang, Kun Ouyang, Lin Jing, Sijie Ruan, Ye Liu, Junbo Zhang, David S. Rosenblum, Yu Zheng:
UrbanFM: Inferring Fine-Grained Urban Flows. 3132-3142 - Haipeng Chen, Rui Liu, Noseong Park, V. S. Subrahmanian:
Using Twitter to Predict When Vulnerabilities will be Exploited. 3143-3152 - Weicong Ding, Dinesh Govindaraj, S. V. N. Vishwanathan:
Whole Page Optimization with Global Constraints. 3153-3161
Applied Data Science Invited Talks
- Carlos Guestrin:
4 Perspectives in Human-Centered Machine Learning. 3162 - Joseph Bradley:
Addressing Challenges in Data Science: Scale, Skill Sets and Complexity. 3163 - Ashok Srivastava:
AI for Small Businesses and Consumers: Applications and Innovations. 3164 - Hongxia Yang:
AliGraph: A Comprehensive Graph Neural Network Platform. 3165-3166 - Ganesh Thondikulam:
Analytics Journey Map: An Approach Enable to ML at Scale. 3167 - Hassan Sawaf:
Applications of AI/ML in Established and New Industries. 3168 - Kumar Chellapilla:
Building a Better Self-Driving Car: Hardware, Software, and Knowledge. 3169 - Ya Xu:
Data Science Challenges @ LinkedIn. 3170 - Ramakrishna R. Nemani:
Earth Observations from a New Generation of Geostationary Satellites. 3171 - David Heckerman:
Exploiting High Dimensionality in Big Data. 3172 - Paige Maas:
Facebook Disaster Maps: Aggregate Insights for Crisis Response & Recovery. 3173 - Richard Caruana:
Friends Don't Let Friends Deploy Black-Box Models: The Importance of Intelligibility in Machine Learning. 3174 - Neel Sundaresan:
From Code to Data: AI at Scale for Developer Productivity. 3175 - Ruslan Salakhutdinov:
Integrating Domain-Knowledge into Deep Learning. 3176 - Olga Liakhovich, Gabriel Domínguez-Conde:
Preventing Rhino Poaching through Machine Learning. 3177 - Rómer Rosales:
Product Ecosystem Optimization at LinkedIn. 3178 - Yinglong Xia:
Roll of Unified Graph Analysis Platforms. 3179 - Elena Grewal:
Seven Years of Data Science at Airbnb. 3180 - Jairam Ranganathan:
Spinning the AI Pinwheel. 3181 - Konstantinos Katsiapis, Kevin Haas:
Towards ML Engineering with TensorFlow Extended (TFX). 3182 - Jieping Ye:
Transportation: A Data Driven Approach. 3183 - Sreenivas Gollapudi:
Welfare Maximization in Online Two-sided Marketplaces. 3184
Tutorials
- Bogdan Cautis, Silviu Maniu, Nikolaos Tziortziotis:
Adaptive Influence Maximization. 3185-3186 - Hsuan-Tien Lin:
Advances in Cost-sensitive Multiclass and Multilabel Classification. 3187-3188 - Xiaolin Shi, Pavel A. Dmitriev, Somit Gupta, Xin Fu:
Challenges, Best Practices and Pitfalls in Evaluating Results of Online Controlled Experiments. 3189-3190 - Jingbo Shang, Jiaming Shen, Liyuan Liu, Jiawei Han:
Constructing and Mining Heterogeneous Information Networks from Massive Text. 3191-3192 - Xin Luna Dong, Theodoros Rekatsinas:
Data Integration and Machine Learning: A Natural Synergy. 3193-3194 - Cao Xiao, Jimeng Sun:
Tutorial: Data Mining Methods for Drug Discovery and Development. 3195-3196 - Jen-Tzung Chien:
Deep Bayesian Mining, Learning and Understanding. 3197-3198 - Weiwei Guo, Huiji Gao, Jun Shi, Bo Long, Liang Zhang, Bee-Chung Chen, Deepak Agarwal:
Deep Natural Language Processing for Search and Recommender Systems. 3199-3200 - Zhiwei (Tony) Qin, Jian Tang, Jieping Ye:
Deep Reinforcement Learning with Applications in Transportation. 3201-3202 - Krishna Gade, Sahin Cem Geyik, Krishnaram Kenthapadi, Varun Mithal, Ankur Taly:
Explainable AI in Industry. 3203-3204 - Sarah Bird, Ben Hutchinson, Krishnaram Kenthapadi, Emre Kiciman, Margaret Mitchell:
Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned. 3205-3206 - Reza Zafarani, Xinyi Zhou, Kai Shu, Huan Liu:
Fake News Research: Theories, Detection Strategies, and Open Problems. 3207-3208 - Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang:
Forecasting Big Time Series: Theory and Practice. 3209-3210 - Aaditya Ramdas:
Foundations of Large-Scale Sequential Experimentation. 3211-3212 - Dawei Zhou, Jingrui He:
Gold Panning from the Mess: Rare Category Exploration, Exposition, Representation, and Interpretation. 3213-3214 - Leonardo Pellegrina, Matteo Riondato, Fabio Vandin:
Hypothesis Testing and Statistically-sound Pattern Mining. 3215-3216 - Tina Eliassi-Rad, Rajmonda Sulo Caceres, Timothy LaRock:
Incompleteness in Networks: Biases, Skewed Results, and Some Solutions. 3217-3218 - Boris Kovalerchuk:
Interpretable Knowledge Discovery Reinforced by Visual Methods. 3219-3220 - Xiao Huang, Peng Cui, Yuxiao Dong, Jundong Li, Huan Liu, Jian Pei, Le Song, Jie Tang, Fei Wang, Hongxia Yang, Wenwu Zhu:
Learning From Networks: Algorithms, Theory, and Applications. 3221-3222 - Myra Spiliopoulou, Panagiotis Papapetrou:
Mining and Model Understanding on Medical Data. 3223-3224 - Polina Rozenshtein, Aristides Gionis:
Mining Temporal Networks. 3225-3226 - Junchi Yan, Hongteng Xu, Liangda Li:
Modeling and Applications for Temporal Point Processes. 3227-3228 - Jilles Vreeken, Kenji Yamanishi:
Modern MDL meets Data Mining Insights, Theory, and Practice. 3229-3230 - Yao Zhou, Fenglong Ma, Jing Gao, Jingrui He:
Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching. 3231-3232 - Pin-Yu Chen, Sijia Liu:
Recent Progress in Zeroth Order Optimization and Its Applications to Adversarial Robustness in Data Mining and Machine Learning. 3233-3234 - Fattane Zarrinkalam, Hossein Fani, Ebrahim Bagheri:
Social User Interest Mining: Methods and Applications. 3235-3236 - Yue Ning, Liang Zhao, Feng Chen, Chang-Tien Lu, Huzefa Rangwala:
Spatio-temporal Event Forecasting and Precursor Identification. 3237-3238 - Charles H. Martin, Michael W. Mahoney:
Statistical Mechanics Methods for Discovering Knowledge from Modern Production Quality Neural Networks. 3239-3240 - David C. Anastasiu, Huzefa Rangwala, Andrea Tagarelli:
Tutorial: Are You My Neighbor?: Bringing Order to Neighbor Computing Problems. 3241-3242
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