| 2019 | 150 Successful Machine Learning Models: 6 Lessons Learned at Booking.com. Lucas Bernardi, Themistoklis Mavridis, Pablo Estevez |
| 2019 | 4 Perspectives in Human-Centered Machine Learning. Carlos Guestrin |
| 2019 | A Collaborative Learning Framework to Tag Refinement for Points of Interest. Jingbo Zhou, Shan Gou, Renjun Hu, Dongxiang Zhang, Jin Xu, Airong Jiang, Ying Li, Hui Xiong |
| 2019 | A Data-Driven Approach for Multi-level Packing Problems in Manufacturing Industry. Lei Chen, Xialiang Tong, Mingxuan Yuan, Jia Zeng, Lei Chen |
| 2019 | A Deep Generative Approach to Search Extrapolation and Recommendation. Fred X. Han, Di Niu, Haolan Chen, Kunfeng Lai, Yancheng He, Yu Xu |
| 2019 | A Deep Value-network Based Approach for Multi-Driver Order Dispatching. Xiaocheng Tang, Zhiwei (Tony) Qin, Fan Zhang, Zhaodong Wang, Zhe Xu, Yintai Ma, Hongtu Zhu, Jieping Ye |
| 2019 | A Free Energy Based Approach for Distance Metric Learning. Sho Inaba, Carl Tony Fakhry, Rahul V. Kulkarni, Kourosh Zarringhalam |
| 2019 | A Generalized Framework for Population Based Training. Ang Li, Ola Spyra, Sagi Perel, Valentin Dalibard, Max Jaderberg, Chenjie Gu, David Budden, Tim Harley, Pramod Gupta |
| 2019 | A Hierarchical Career-Path-Aware Neural Network for Job Mobility Prediction. Qingxin Meng, Hengshu Zhu, Keli Xiao, Le Zhang, Hui Xiong |
| 2019 | A Memory-Efficient Sketch Method for Estimating High Similarities in Streaming Sets. Pinghui Wang, Yiyan Qi, Yuanming Zhang, Qiaozhu Zhai, Chenxu Wang, John C. S. Lui, Xiaohong Guan |
| 2019 | A Minimax Game for Instance based Selective Transfer Learning. Bo Wang, Minghui Qiu, Xisen Wang, Yaliang Li, Yu Gong, Xiaoyi Zeng, Jun Huang, Bo Zheng, Deng Cai, Jingren Zhou |
| 2019 | A Multiscale Scan Statistic for Adaptive Submatrix Localization. Yuchao Liu, Ery Arias-Castro |
| 2019 | A Permutation Approach to Assess Confounding in Machine Learning Applications for Digital Health. Elias Chaibub Neto, Abhishek Pratap, Thanneer M. Perumal, Meghasyam Tummalacherla, Brian M. Bot, Lara M. Mangravite, Larsson Omberg |
| 2019 | A Representation Learning Framework for Property Graphs. Yifan Hou, Hongzhi Chen, Changji Li, James Cheng, Ming-Chang Yang |
| 2019 | A Robust Framework for Accelerated Outcome-driven Risk Factor Identification from EHR. Prithwish Chakraborty, Faisal Farooq |
| 2019 | A Severity Score for Retinopathy of Prematurity. Peng Tian, Yuan Guo, Jayashree Kalpathy-Cramer, Susan Ostmo, John Peter Campbell, Michael F. Chiang, Jennifer G. Dy, Deniz Erdogmus, Stratis Ioannidis |
| 2019 | A Unified Framework for Marketing Budget Allocation. Kui Zhao, Junhao Hua, Ling Yan, Qi Zhang, Huan Xu, Cheng Yang |
| 2019 | A User-Centered Concept Mining System for Query and Document Understanding at Tencent. Bang Liu, Weidong Guo, Di Niu, Chaoyue Wang, Shunnan Xu, Jinghong Lin, Kunfeng Lai, Yu Xu |
| 2019 | A Visual Dialog Augmented Interactive Recommender System. Tong Yu, Yilin Shen, Hongxia Jin |
| 2019 | ADMM for Efficient Deep Learning with Global Convergence. Junxiang Wang, Fuxun Yu, Xiang Chen, Liang Zhao |
| 2019 | AI for Small Businesses and Consumers: Applications and Innovations. Ashok Srivastava |
| 2019 | AKUPM: Attention-Enhanced Knowledge-Aware User Preference Model for Recommendation. Xiaoli Tang, Tengyun Wang, Haizhi Yang, Hengjie Song |
| 2019 | AccuAir: Winning Solution to Air Quality Prediction for KDD Cup 2018. Zhipeng Luo, Jianqiang Huang, Ke Hu, Xue Li, Peng Zhang |
| 2019 | Actions Speak Louder than Goals: Valuing Player Actions in Soccer. Tom Decroos, Lotte Bransen, Jan Van Haaren, Jesse Davis |
| 2019 | Active Deep Learning for Activity Recognition with Context Aware Annotator Selection. H. M. Sajjad Hossain, Nirmalya Roy |
| 2019 | Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability. Yang Yang, Da-Wei Zhou, De-Chuan Zhan, Hui Xiong, Yuan Jiang |
| 2019 | Adaptive Graph Guided Disambiguation for Partial Label Learning. Deng-Bao Wang, Li Li, Min-Ling Zhang |
| 2019 | Adaptive Influence Maximization. Bogdan Cautis, Silviu Maniu, Nikolaos Tziortziotis |
| 2019 | Adaptive Unsupervised Feature Selection on Attributed Networks. Jundong Li, Ruocheng Guo, Chenghao Liu, Huan Liu |
| 2019 | Adaptive-Halting Policy Network for Early Classification. Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner |
| 2019 | Addressing Challenges in Data Science: Scale, Skill Sets and Complexity. Joseph Bradley |
| 2019 | Advances in Cost-sensitive Multiclass and Multilabel Classification. Hsuan-Tien Lin |
| 2019 | Adversarial Learning on Heterogeneous Information Networks. Binbin Hu, Yuan Fang, Chuan Shi |
| 2019 | Adversarial Matching of Dark Net Market Vendor Accounts. Xiao Hui Tai, Kyle Soska, Nicolas Christin |
| 2019 | Adversarial Substructured Representation Learning for Mobile User Profiling. Pengyang Wang, Yanjie Fu, Hui Xiong, Xiaolin Li |
| 2019 | Adversarial Variational Embedding for Robust Semi-supervised Learning. Xiang Zhang, Lina Yao, Feng Yuan |
| 2019 | Adversarially Robust Submodular Maximization under Knapsack Constraints. Dmitrii Avdiukhin, Slobodan Mitrovic, Grigory Yaroslavtsev, Samson Zhou |
| 2019 | AiAds: Automated and Intelligent Advertising System for Sponsored Search. Xiao Yang, Daren Sun, Ruiwei Zhu, Tao Deng, Zhi Guo, Zongyao Ding, Shouke Qin, Yanfeng Zhu |
| 2019 | AliGraph: A Comprehensive Graph Neural Network Platform. Hongxia Yang |
| 2019 | AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks. Jingyuan Wang, Yang Zhang, Ke Tang, Junjie Wu, Zhang Xiong |
| 2019 | Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning. Yichen Shen, Maxime Voisin, Alireza Aliamiri, Anand Avati, Awni Y. Hannun, Andrew Y. Ng |
| 2019 | Analytics Journey Map: An Approach Enable to ML at Scale. Ganesh Thondikulam |
| 2019 | Anomaly Detection for an E-commerce Pricing System. Jagdish Ramakrishnan, Elham Shaabani, Chao Li, Mátyás A. Sustik |
| 2019 | Applications of AI/ML in Established and New Industries. Hassan Sawaf |
| 2019 | Applying Deep Learning to Airbnb Search. 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 |
| 2019 | Assessing The Factual Accuracy of Generated Text. Ben Goodrich, Vinay Rao, Peter J. Liu, Mohammad Saleh |
| 2019 | AtSNE: Efficient and Robust Visualization on GPU through Hierarchical Optimization. Cong Fu, Yonghui Zhang, Deng Cai, Xiang Ren |
| 2019 | Attribute-Driven Backbone Discovery. Sheng Guan, Hanchao Ma, Yinghui Wu |
| 2019 | Auditing Data Provenance in Text-Generation Models. Congzheng Song, Vitaly Shmatikov |
| 2019 | Auto-Keras: An Efficient Neural Architecture Search System. Haifeng Jin, Qingquan Song, Xia Hu |
| 2019 | AutoCross: Automatic Feature Crossing for Tabular Data in Real-World Applications. Yuanfei Luo, Mengshuo Wang, Hao Zhou, Quanming Yao, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang |
| 2019 | AutoNE: Hyperparameter Optimization for Massive Network Embedding. Ke Tu, Jianxin Ma, Peng Cui, Jian Pei, Wenwu Zhu |
| 2019 | Automatic Dialogue Summary Generation for Customer Service. Chunyi Liu, Peng Wang, Jiang Xu, Zang Li, Jieping Ye |
| 2019 | Automating Feature Subspace Exploration via Multi-Agent Reinforcement Learning. Kunpeng Liu, Yanjie Fu, Pengfei Wang, Le Wu, Rui Bo, Xiaolin Li |
| 2019 | Axiomatic Interpretability for Multiclass Additive Models. Xuezhou Zhang, Sarah Tan, Paul Koch, Yin Lou, Urszula Chajewska, Rich Caruana |
| 2019 | Beyond Personalization: Social Content Recommendation for Creator Equality and Consumer Satisfaction. Wenyi Xiao, Huan Zhao, Haojie Pan, Yangqiu Song, Vincent W. Zheng, Qiang Yang |
| 2019 | Bid Optimization by Multivariable Control in Display Advertising. Xun Yang, Yasong Li, Hao Wang, Di Wu, Qing Tan, Jian Xu, Kun Gai |
| 2019 | Blending Noisy Social Media Signals with Traditional Movement Variables to Predict Forced Migration. Lisa Singh, Laila Wahedi, Yanchen Wang, Yifang Wei, Christo Kirov, Susan Martin, Katharine M. Donato, Yaguang Liu, Kornraphop Kawintiranon |
| 2019 | Building a Better Self-Driving Car: Hardware, Software, and Knowledge. Kumar Chellapilla |
| 2019 | Buying or Browsing?: Predicting Real-time Purchasing Intent using Attention-based Deep Network with Multiple Behavior. Long Guo, Lifeng Hua, Rongfei Jia, Binqiang Zhao, Xiaobo Wang, Bin Cui |
| 2019 | Carousel Ads Optimization in Yahoo Gemini Native. Michal Aharon, Oren Somekh, Avi Shahar, Assaf Singer, Baruch Trayvas, Hadas Vogel, Dobri Dobrev |
| 2019 | Certifiable Robustness and Robust Training for Graph Convolutional Networks. Daniel Zügner, Stephan Günnemann |
| 2019 | Chainer: A Deep Learning Framework for Accelerating the Research Cycle. Seiya Tokui, Ryosuke Okuta, Takuya Akiba, Yusuke Niitani, Toru Ogawa, Shunta Saito, Shuji Suzuki, Kota Uenishi, Brian Vogel, Hiroyuki Yamazaki Vincent |
| 2019 | Challenges, Best Practices and Pitfalls in Evaluating Results of Online Controlled Experiments. Xiaolin Shi, Pavel A. Dmitriev, Somit Gupta, Xin Fu |
| 2019 | Characterizing and Detecting Malicious Accounts in Privacy-Centric Mobile Social Networks: A Case Study. Zenghua Xia, Chang Liu, Neil Zhenqiang Gong, Qi Li, Yong Cui, Dawn Song |
| 2019 | Characterizing and Forecasting User Engagement with In-App Action Graph: A Case Study of Snapchat. Yozen Liu, Xiaolin Shi, Lucas Pierce, Xiang Ren |
| 2019 | Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks. Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh |
| 2019 | Clustering without Over-Representation. Sara Ahmadian, Alessandro Epasto, Ravi Kumar, Mohammad Mahdian |
| 2019 | Co-Prediction of Multiple Transportation Demands Based on Deep Spatio-Temporal Neural Network. Junchen Ye, Leilei Sun, Bowen Du, Yanjie Fu, Xinran Tong, Hui Xiong |
| 2019 | CoSTCo: A Neural Tensor Completion Model for Sparse Tensors. Hanpeng Liu, Yaguang Li, Michael Tsang, Yan Liu |
| 2019 | Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search. Pan Li, Zhen Qin, Xuanhui Wang, Donald Metzler |
| 2019 | Community Detection on Large Complex Attribute Network. Zhe Chen, Aixin Sun, Xiaokui Xiao |
| 2019 | Conditional Random Field Enhanced Graph Convolutional Neural Networks. Hongchang Gao, Jian Pei, Heng Huang |
| 2019 | Constructing High Precision Knowledge Bases with Subjective and Factual Attributes. Ari Kobren, Pablo Barrio, Oksana Yakhnenko, Johann Hibschman, Ian Langmore |
| 2019 | Constructing and Mining Heterogeneous Information Networks from Massive Text. Jingbo Shang, Jiaming Shen, Liyuan Liu, Jiawei Han |
| 2019 | Context by Proxy: Identifying Contextual Anomalies Using an Output Proxy. Jan-Philipp Schulze, Artur Mrowca, Elizabeth Ren, Hans-Andrea Loeliger, Konstantin Böttinger |
| 2019 | Contextual Fact Ranking and Its Applications in Table Synthesis and Compression. Silu Huang, Jialu Liu, Flip Korn, Xuezhi Wang, You Wu, Dale Markowitz, Cong Yu |
| 2019 | Contrastive Antichains in Hierarchies. Anes Bendimerad, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie |
| 2019 | Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creatives. Shunsuke Kitada, Hitoshi Iyatomi, Yoshifumi Seki |
| 2019 | Coresets for Minimum Enclosing Balls over Sliding Windows. Yanhao Wang, Yuchen Li, Kian-Lee Tan |
| 2019 | Coupled Variational Recurrent Collaborative Filtering. Qingquan Song, Shiyu Chang, Xia Hu |
| 2019 | DAML: Dual Attention Mutual Learning between Ratings and Reviews for Item Recommendation. Donghua Liu, Jing Li, Bo Du, Jun Chang, Rong Gao |
| 2019 | DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification. Jun Wu, Jingrui He, Jiejun Xu |
| 2019 | Data Integration and Machine Learning: A Natural Synergy. Xin Luna Dong, Theodoros Rekatsinas |
| 2019 | Data Science Challenges @ LinkedIn. Ya Xu |
| 2019 | Deep Anomaly Detection with Deviation Networks. Guansong Pang, Chunhua Shen, Anton van den Hengel |
| 2019 | Deep Bayesian Mining, Learning and Understanding. Jen-Tzung Chien |
| 2019 | Deep Landscape Forecasting for Real-time Bidding Advertising. Kan Ren, Jiarui Qin, Lei Zheng, Zhengyu Yang, Weinan Zhang, Yong Yu |
| 2019 | Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information. Maya Okawa, Tomoharu Iwata, Takeshi Kurashima, Yusuke Tanaka, Hiroyuki Toda, Naonori Ueda |
| 2019 | Deep Natural Language Processing for Search and Recommender Systems. Weiwei Guo, Huiji Gao, Jun Shi, Bo Long, Liang Zhang, Bee-Chung Chen, Deepak Agarwal |
| 2019 | Deep Reinforcement Learning with Applications in Transportation. Zhiwei (Tony) Qin, Jian Tang, Jieping Ye |
| 2019 | Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction. Wentao Ouyang, Xiuwu Zhang, Li Li, Heng Zou, Xin Xing, Zhaojie Liu, Yanlong Du |
| 2019 | Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting. Bin Wang, Jie Lu, Zheng Yan, Huaishao Luo, Tianrui Li, Yu Zheng, Guangquan Zhang |
| 2019 | DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks. Guolin Ke, Zhenhui Xu, Jia Zhang, Jiang Bian, Tie-Yan Liu |
| 2019 | DeepHoops: Evaluating Micro-Actions in Basketball Using Deep Feature Representations of Spatio-Temporal Data. Anthony Sicilia, Konstantinos Pelechrinis, Kirk Goldsberry |
| 2019 | DeepRoof: A Data-driven Approach For Solar Potential Estimation Using Rooftop Imagery. Stephen Lee, Srinivasan Iyengar, Menghong Feng, Prashant J. Shenoy, Subhransu Maji |
| 2019 | DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big Events. Renhe Jiang, Xuan Song, Dou Huang, Xiaoya Song, Tianqi Xia, Zekun Cai, Zhaonan Wang, Kyoung-Sook Kim, Ryosuke Shibasaki |
| 2019 | Detecting Anomalies in Space using Multivariate Convolutional LSTM with Mixtures of Probabilistic PCA. Shahroz Tariq, Sangyup Lee, Youjin Shin, Myeong Shin Lee, Okchul Jung, Daewon Chung, Simon S. Woo |
| 2019 | Detection of Review Abuse via Semi-Supervised Binary Multi-Target Tensor Decomposition. Anil R. Yelundur, Vineet Chaoji, Bamdev Mishra |
| 2019 | Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams. 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 |
| 2019 | Diagnosing Sample Ratio Mismatch in Online Controlled Experiments: A Taxonomy and Rules of Thumb for Practitioners. Aleksander Fabijan, Jayant Gupchup, Somit Gupta, Jeff Omhover, Wen Qin, Lukas Vermeer, Pavel A. Dmitriev |
| 2019 | Disambiguation Enabled Linear Discriminant Analysis for Partial Label Dimensionality Reduction. Jing-Han Wu, Min-Ling Zhang |
| 2019 | Discovering Unexpected Local Nonlinear Interactions in Scientific Black-box Models. Michael Doron, Idan Segev, Dafna Shahaf |
| 2019 | Do Simpler Models Exist and How Can We Find Them? Cynthia Rudin |
| 2019 | Dual Averaging Method for Online Graph-structured Sparsity. Baojian Zhou, Feng Chen, Yiming Ying |
| 2019 | Dual Sequential Prediction Models Linking Sequential Recommendation and Information Dissemination. Qitian Wu, Yirui Gao, Xiaofeng Gao, Paul Weng, Guihai Chen |
| 2019 | DuerQuiz: A Personalized Question Recommender System for Intelligent Job Interview. Chuan Qin, Hengshu Zhu, Chen Zhu, Tong Xu, Fuzhen Zhuang, Chao Ma, Jingshuai Zhang, Hui Xiong |
| 2019 | Dynamic Modeling and Forecasting of Time-evolving Data Streams. Yasuko Matsubara, Yasushi Sakurai |
| 2019 | Dynamic Pricing for Airline Ancillaries with Customer Context. Naman Shukla, Arinbjörn Kolbeinsson, Ken Otwell, Lavanya Marla, Kartik Yellepeddi |
| 2019 | Dynamical Origins of Distribution Functions. Chengxi Zang, Peng Cui, Wenwu Zhu, Fei Wang |
| 2019 | E.T.-RNN: Applying Deep Learning to Credit Loan Applications. Dmitrii Babaev, Maxim Savchenko, Alexander Tuzhilin, Dmitrii Umerenkov |
| 2019 | ET-Lasso: A New Efficient Tuning of Lasso-type Regularization for High-Dimensional Data. Songshan Yang, Jiawei Wen, Xiang Zhan, Daniel Kifer |
| 2019 | Earth Observations from a New Generation of Geostationary Satellites. Ramakrishna R. Nemani |
| 2019 | EdMot: An Edge Enhancement Approach for Motif-aware Community Detection. Pei-Zhen Li, Ling Huang, Chang-Dong Wang, Jian-Huang Lai |
| 2019 | Effective and Efficient Reuse of Past Travel Behavior for Route Recommendation. Lisi Chen, Shuo Shang, Christian S. Jensen, Bin Yao, Zhiwei Zhang, Ling Shao |
| 2019 | Effective and Efficient Sports Play Retrieval with Deep Representation Learning. Zheng Wang, Cheng Long, Gao Cong, Ce Ju |
| 2019 | Efficient Global String Kernel with Random Features: Beyond Counting Substructures. Lingfei Wu, Ian En-Hsu Yen, Siyu Huo, Liang Zhao, Kun Xu, Liang Ma, Shouling Ji, Charu C. Aggarwal |
| 2019 | Efficient Maximum Clique Computation over Large Sparse Graphs. Lijun Chang |
| 2019 | Efficient and Effective Express via Contextual Cooperative Reinforcement Learning. Yexin Li, Yu Zheng, Qiang Yang |
| 2019 | Empowering A* Search Algorithms with Neural Networks for Personalized Route Recommendation. Jingyuan Wang, Ning Wu, Wayne Xin Zhao, Fanzhang Peng, Xin Lin |
| 2019 | Enabling Onboard Detection of Events of Scientific Interest for the Europa Clipper Spacecraft. Kiri L. Wagstaff, Gary Doran, Ashley Davies, Saadat Anwar, Srija Chakraborty, Marissa Cameron, Ingrid Daubar, Cynthia A. Phillips |
| 2019 | Enhancing Collaborative Filtering with Generative Augmentation. Qinyong Wang, Hongzhi Yin, Hao Wang, Quoc Viet Hung Nguyen, Zi Huang, Lizhen Cui |
| 2019 | Enhancing Domain Word Embedding via Latent Semantic Imputation. Shibo Yao, Dantong Yu, Keli Xiao |
| 2019 | Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation. Wenjie Shang, Yang Yu, Qingyang Li, Zhiwei (Tony) Qin, Yiping Meng, Jieping Ye |
| 2019 | EpiDeep: Exploiting Embeddings for Epidemic Forecasting. Bijaya Adhikari, Xinfeng Xu, Naren Ramakrishnan, B. Aditya Prakash |
| 2019 | Estimating Cellular Goals from High-Dimensional Biological Data. Laurence Yang, Michael A. Saunders, Jean-Christophe Lachance, Bernhard O. Palsson, José Bento |
| 2019 | Estimating Graphlet Statistics via Lifting. Kirill Paramonov, Dmitry Shemetov, James Sharpnack |
| 2019 | Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks. Namyong Park, Andrey Kan, Xin Luna Dong, Tong Zhao, Christos Faloutsos |
| 2019 | Exact-K Recommendation via Maximal Clique Optimization. Yu Gong, Yu Zhu, Lu Duan, Qingwen Liu, Ziyu Guan, Fei Sun, Wenwu Ou, Kenny Q. Zhu |
| 2019 | Explainable AI in Industry. Krishna Gade, Sahin Cem Geyik, Krishnaram Kenthapadi, Varun Mithal, Ankur Taly |
| 2019 | Exploiting Cognitive Structure for Adaptive Learning. Qi Liu, Shiwei Tong, Chuanren Liu, Hongke Zhao, Enhong Chen, Haiping Ma, Shijin Wang |
| 2019 | Exploiting High Dimensionality in Big Data. David Heckerman |
| 2019 | FDML: A Collaborative Machine Learning Framework for Distributed Features. Yaochen Hu, Di Niu, Jianming Yang, Shengping Zhou |
| 2019 | Facebook Disaster Maps: Aggregate Insights for Crisis Response & Recovery. Paige Maas |
| 2019 | Factorization Bandits for Online Influence Maximization. Qingyun Wu, Zhige Li, Huazheng Wang, Wei Chen, Hongning Wang |
| 2019 | Fairness in Recommendation Ranking through Pairwise Comparisons. Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H. Chi, Cristos Goodrow |
| 2019 | Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned. Sarah Bird, Ben Hutchinson, Krishnaram Kenthapadi, Emre Kiciman, Margaret Mitchell |
| 2019 | Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search. Sahin Cem Geyik, Stuart Ambler, Krishnaram Kenthapadi |
| 2019 | Fake News Research: Theories, Detection Strategies, and Open Problems. Reza Zafarani, Xinyi Zhou, Kai Shu, Huan Liu |
| 2019 | Fast Approximation of Empirical Entropy via Subsampling. Chi Wang, Bailu Ding |
| 2019 | Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach. Minji Yoon, Bryan Hooi, Kijung Shin, Christos Faloutsos |
| 2019 | Fates of Microscopic Social Ecosystems: Keep Alive or Dead? Haoyang Li, Peng Cui, Chengxi Zang, Tianyang Zhang, Wenwu Zhu, Yishi Lin |
| 2019 | Feedback Shaping: A Modeling Approach to Nurture Content Creation. Ye Tu, Chun Lo, Yiping Yuan, Shaunak Chatterjee |
| 2019 | Fighting Opinion Control in Social Networks via Link Recommendation. Victor Amelkin, Ambuj K. Singh |
| 2019 | Figuring out the User in a Few Steps: Bayesian Multifidelity Active Search with Cokriging. Nikita Klyuchnikov, Davide Mottin, Georgia Koutrika, Emmanuel Müller, Panagiotis Karras |
| 2019 | Finding Users Who Act Alike: Transfer Learning for Expanding Advertiser Audiences. Stephanie deWet, Jiafan Ou |
| 2019 | Focused Context Balancing for Robust Offline Policy Evaluation. Hao Zou, Kun Kuang, Boqi Chen, Peixuan Chen, Peng Cui |
| 2019 | FoodAI: Food Image Recognition via Deep Learning for Smart Food Logging. Doyen Sahoo, Hao Wang, Shu Ke, Xiongwei Wu, Hung Le, Palakorn Achananuparp, Ee-Peng Lim, Steven C. H. Hoi |
| 2019 | Forecasting Big Time Series: Theory and Practice. Christos Faloutsos, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Yuyang Wang |
| 2019 | Foundations of Large-Scale Sequential Experimentation. Aaditya Ramdas |
| 2019 | Friends Don't Let Friends Deploy Black-Box Models: The Importance of Intelligibility in Machine Learning. Richard Caruana |
| 2019 | From Code to Data: AI at Scale for Developer Productivity. Neel Sundaresan |
| 2019 | GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization. Peng Han, Peng Yang, Peilin Zhao, Shuo Shang, Yong Liu, Jiayu Zhou, Xin Gao, Panos Kalnis |
| 2019 | Generating Better Search Engine Text Advertisements with Deep Reinforcement Learning. J. Weston Hughes, Keng-hao Chang, Ruofei Zhang |
| 2019 | Glaucoma Progression Prediction Using Retinal Thickness via Latent Space Linear Regression. Yuhui Zheng, Linchuan Xu, Taichi Kiwaki, Jing Wang, Hiroshi Murata, Ryo Asaoka, Kenji Yamanishi |
| 2019 | Gmail Smart Compose: Real-Time Assisted Writing. 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 |
| 2019 | Gold Panning from the Mess: Rare Category Exploration, Exposition, Representation, and Interpretation. Dawei Zhou, Jingrui He |
| 2019 | Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Zaheer, Daniel Silva, Andrew McCallum, Amr Ahmed |
| 2019 | Graph Convolutional Networks with EigenPooling. Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang |
| 2019 | Graph Recurrent Networks With Attributed Random Walks. Xiao Huang, Qingquan Song, Yuening Li, Xia Hu |
| 2019 | Graph Representation Learning via Hard and Channel-Wise Attention Networks. Hongyang Gao, Shuiwang Ji |
| 2019 | Graph Transformation Policy Network for Chemical Reaction Prediction. Kien Do, Truyen Tran, Svetha Venkatesh |
| 2019 | Graph-based Semi-Supervised & Active Learning for Edge Flows. Junteng Jia, Michael T. Schaub, Santiago Segarra, Austin R. Benson |
| 2019 | GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data. Yujun Yan, Jiong Zhu, Marlena Duda, Eric Solarz, Chandra Sekhar Sripada, Danai Koutra |
| 2019 | HATS: A Hierarchical Sequence-Attention Framework for Inductive Set-of-Sets Embeddings. Changping Meng, Jiasen Yang, Bruno Ribeiro, Jennifer Neville |
| 2019 | Hard to Park?: Estimating Parking Difficulty at Scale. Neha Arora, James Cook, Ravi Kumar, Ivan Kuznetsov, Yechen Li, Huai-Jen Liang, Andrew Miller, Andrew Tomkins, Iveel Tsogsuren, Yi Wang |
| 2019 | Heterogeneous Graph Neural Network. Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami, Nitesh V. Chawla |
| 2019 | Hidden Markov Contour Tree: A Spatial Structured Model for Hydrological Applications. Zhe Jiang, Arpan Man Sainju |
| 2019 | Hidden POI Ranking with Spatial Crowdsourcing. Yue Cui, Liwei Deng, Yan Zhao, Bin Yao, Vincent W. Zheng, Kai Zheng |
| 2019 | Hierarchical Gating Networks for Sequential Recommendation. Chen Ma, Peng Kang, Xue Liu |
| 2019 | Hierarchical Multi-Task Word Embedding Learning for Synonym Prediction. Hongliang Fei, Shulong Tan, Ping Li |
| 2019 | How to Invest my Time: Lessons from Human-in-the-Loop Entity Extraction. Shanshan Zhang, Lihong He, Eduard C. Dragut, Slobodan Vucetic |
| 2019 | Hydra: A Personalized and Context-Aware Multi-Modal Transportation Recommendation System. Hao Liu, Yongxin Tong, Panpan Zhang, Xinjiang Lu, Jianguo Duan, Hui Xiong |
| 2019 | Hypothesis Generation From Text Based On Co-Evolution Of Biomedical Concepts. Kishlay Jha, Guangxu Xun, Yaqing Wang, Aidong Zhang |
| 2019 | Hypothesis Testing and Statistically-sound Pattern Mining. Leonardo Pellegrina, Matteo Riondato, Fabio Vandin |
| 2019 | IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery. Dipendra Jha, Logan T. Ward, Zijiang Yang, Christopher Wolverton, Ian T. Foster, Wei-keng Liao, Alok N. Choudhary, Ankit Agrawal |
| 2019 | Identifiability of Cause and Effect using Regularized Regression. Alexander Marx, Jilles Vreeken |
| 2019 | Improving Subseasonal Forecasting in the Western U.S. with Machine Learning. Jessica Hwang, Paulo Orenstein, Judah Cohen, Karl Pfeiffer, Lester Mackey |
| 2019 | Improving the Quality of Explanations with Local Embedding Perturbations. Yunzhe Jia, James Bailey, Kotagiri Ramamohanarao, Christopher Leckie, Michael E. Houle |
| 2019 | Incompleteness in Networks: Biases, Skewed Results, and Some Solutions. Tina Eliassi-Rad, Rajmonda Sulo Caceres, Timothy LaRock |
| 2019 | Incorporating Interpretability into Latent Factor Models via Fast Influence Analysis. Weiyu Cheng, Yanyan Shen, Linpeng Huang, Yanmin Zhu |
| 2019 | Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding. Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu |
| 2019 | Infer Implicit Contexts in Real-time Online-to-Offline Recommendation. Xichen Ding, Jie Tang, Tracy Xiao Liu, Cheng Xu, Yaping Zhang, Feng Shi, Qixia Jiang, Dan Shen |
| 2019 | Integrating Domain-Knowledge into Deep Learning. Ruslan Salakhutdinov |
| 2019 | IntentGC: A Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation. Jun Zhao, Zhou Zhou, Ziyu Guan, Wei Zhao, Wei Ning, Guang Qiu, Xiaofei He |
| 2019 | Internal Promotion Optimization. Rupesh Gupta, Guangde Chen, Shipeng Yu |
| 2019 | Interpretable Knowledge Discovery Reinforced by Visual Methods. Boris Kovalerchuk |
| 2019 | Interpretable and Steerable Sequence Learning via Prototypes. Yao Ming, Panpan Xu, Huamin Qu, Liu Ren |
| 2019 | Interview Choice Reveals Your Preference on the Market: To Improve Job-Resume Matching through Profiling Memories. Rui Yan, Ran Le, Yang Song, Tao Zhang, Xiangliang Zhang, Dongyan Zhao |
| 2019 | Investigate Transitions into Drug Addiction through Text Mining of Reddit Data. John Lu, Sumati Sridhar, Ritika Pandey, Mohammad Al Hasan, George O. Mohler |
| 2019 | Investigating Cognitive Effects in Session-level Search User Satisfaction. Mengyang Liu, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma |
| 2019 | Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction. Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu |
| 2019 | Is a Single Vector Enough?: Exploring Node Polysemy for Network Embedding. Ninghao Liu, Qiaoyu Tan, Yuening Li, Hongxia Yang, Jingren Zhou, Xia Hu |
| 2019 | Isolation Set-Kernel and Its Application to Multi-Instance Learning. Bi-Cun Xu, Kai Ming Ting, Zhi-Hua Zhou |
| 2019 | K-Multiple-Means: A Multiple-Means Clustering Method with Specified K Clusters. Feiping Nie, Cheng-Long Wang, Xuelong Li |
| 2019 | KGAT: Knowledge Graph Attention Network for Recommendation. Xiang Wang, Xiangnan He, Yixin Cao, Meng Liu, Tat-Seng Chua |
| 2019 | Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems. Hongwei Wang, Fuzheng Zhang, Mengdi Zhang, Jure Leskovec, Miao Zhao, Wenjie Li, Zhongyuan Wang |
| 2019 | Large-Scale Training Framework for Video Annotation. Seong Jae Hwang, Joonseok Lee, Balakrishnan Varadarajan, Ariel Gordon, Zheng Xu, Apostol Natsev |
| 2019 | Large-scale User Visits Understanding and Forecasting with Deep Spatial-Temporal Tensor Factorization Framework. Xiaoyang Ma, Lan Zhang, Lan Xu, Zhicheng Liu, Ge Chen, Zhili Xiao, Yang Wang, Zhengtao Wu |
| 2019 | Latent Network Summarization: Bridging Network Embedding and Summarization. Di Jin, Ryan A. Rossi, Eunyee Koh, Sungchul Kim, Anup Rao, Danai Koutra |
| 2019 | Learning Class-Conditional GANs with Active Sampling. Ming-Kun Xie, Sheng-Jun Huang |
| 2019 | Learning Dynamic Context Graphs for Predicting Social Events. Songgaojun Deng, Huzefa Rangwala, Yue Ning |
| 2019 | Learning From Networks: Algorithms, Theory, and Applications. Xiao Huang, Peng Cui, Yuxiao Dong, Jundong Li, Huan Liu, Jian Pei, Le Song, Jie Tang, Fei Wang, Hongxia Yang, Wenwu Zhu |
| 2019 | Learning Interpretable Metric between Graphs: Convex Formulation and Computation with Graph Mining. Tomoki Yoshida, Ichiro Takeuchi, Masayuki Karasuyama |
| 2019 | Learning Network-to-Network Model for Content-rich Network Embedding. Zhicheng He, Jie Liu, Na Li, Yalou Huang |
| 2019 | Learning Sleep Quality from Daily Logs. Sungkyu Park, Cheng-Te Li, Sungwon Han, Cheng Hsu, Sang Won Lee, Meeyoung Cha |
| 2019 | Learning a Unified Embedding for Visual Search at Pinterest. Andrew Zhai, Hao-Yu Wu, Eric Tzeng, Dong Huk Park, Charles Rosenberg |
| 2019 | Learning from Incomplete and Inaccurate Supervision. Zhenyu Zhang, Peng Zhao, Yuan Jiang, Zhi-Hua Zhou |
| 2019 | Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data. Jackson A. Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, Milind Tambe |
| 2019 | LightNet: A Dual Spatiotemporal Encoder Network Model for Lightning Prediction. Yangli-ao Geng, Qingyong Li, Tianyang Lin, Lei Jiang, Liangtao Xu, Dong Zheng, Wen Yao, Weitao Lyu, Yijun Zhang |
| 2019 | Link Prediction with Signed Latent Factors in Signed Social Networks. Pinghua Xu, Wenbin Hu, Jia Wu, Bo Du |
| 2019 | Log2Intent: Towards Interpretable User Modeling via Recurrent Semantics Memory Unit. Zhiqiang Tao, Sheng Li, Zhaowen Wang, Chen Fang, Longqi Yang, Handong Zhao, Yun Fu |
| 2019 | MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network. Hao Wang, Tong Xu, Qi Liu, Defu Lian, Enhong Chen, Dongfang Du, Han Wu, Wen Su |
| 2019 | MOBIUS: Towards the Next Generation of Query-Ad Matching in Baidu's Sponsored Search. Miao Fan, Jiacheng Guo, Shuai Zhu, Shuo Miao, Mingming Sun, Ping Li |
| 2019 | MSURU: Large Scale E-commerce Image Classification with Weakly Supervised Search Data. Yina Tang, Fedor Borisyuk, Siddarth Malreddy, Yixuan Li, Yiqun Liu, Sergey Kirshner |
| 2019 | MVAN: Multi-view Attention Networks for Real Money Trading Detection in Online Games. Jianrong Tao, Jianshi Lin, Shize Zhang, Sha Zhao, Runze Wu, Changjie Fan, Peng Cui |
| 2019 | Machine Learning at Microsoft with ML.NET. 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 |
| 2019 | Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning. Megha Srivastava, Hoda Heidari, Andreas Krause |
| 2019 | MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation. Hoyeop Lee, Jinbae Im, Seongwon Jang, Hyunsouk Cho, Sehee Chung |
| 2019 | MediaRank: Computational Ranking of Online News Sources. Junting Ye, Steven Skiena |
| 2019 | MetaPred: Meta-Learning for Clinical Risk Prediction with Limited Patient Electronic Health Records. Xi Sheryl Zhang, Fengyi Tang, Hiroko H. Dodge, Jiayu Zhou, Fei Wang |
| 2019 | Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation. Shaohua Fan, Junxiong Zhu, Xiaotian Han, Chuan Shi, Linmei Hu, Biyu Ma, Yongliang Li |
| 2019 | MinJoin: Efficient Edit Similarity Joins via Local Hash Minima. Haoyu Zhang, Qin Zhang |
| 2019 | Mining Algorithm Roadmap in Scientific Publications. Hanwen Zha, Wenhu Chen, Keqian Li, Xifeng Yan |
| 2019 | Mining Temporal Networks. Polina Rozenshtein, Aristides Gionis |
| 2019 | Mining and Model Understanding on Medical Data. Myra Spiliopoulou, Panagiotis Papapetrou |
| 2019 | Modeling Dwell Time Engagement on Visual Multimedia. Hemank Lamba, Neil Shah |
| 2019 | Modeling Extreme Events in Time Series Prediction. Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, Xiangnan He |
| 2019 | Modeling and Applications for Temporal Point Processes. Junchi Yan, Hongteng Xu, Liangda Li |
| 2019 | Modern MDL meets Data Mining Insights, Theory, and Practice. Jilles Vreeken, Kenji Yamanishi |
| 2019 | Multi-Horizon Time Series Forecasting with Temporal Attention Learning. Chenyou Fan, Yuze Zhang, Yi Pan, Xiaoyue Li, Chi Zhang, Rong Yuan, Di Wu, Wensheng Wang, Jian Pei, Heng Huang |
| 2019 | Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings. Ahmed Rashed, Josif Grabocka, Lars Schmidt-Thieme |
| 2019 | 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. Chang Li, Dongjin Song, Dacheng Tao |
| 2019 | Multiple Relational Attention Network for Multi-task Learning. Jiejie Zhao, Bowen Du, Leilei Sun, Fuzhen Zhuang, Weifeng Lv, Hui Xiong |
| 2019 | NPA: Neural News Recommendation with Personalized Attention. Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang, Xing Xie |
| 2019 | Naranjo Question Answering using End-to-End Multi-task Learning Model. Bhanu Pratap Singh Rawat, Fei Li, Hong Yu |
| 2019 | Network Density of States. Kun Dong, Austin R. Benson, David Bindel |
| 2019 | NodeSketch: Highly-Efficient Graph Embeddings via Recursive Sketching. Dingqi Yang, Paolo Rosso, Bin Li, Philippe Cudré-Mauroux |
| 2019 | Nonparametric Mixture of Sparse Regressions on Spatio-Temporal Data - An Application to Climate Prediction. Yumin Liu, Junxiang Chen, Auroop R. Ganguly, Jennifer G. Dy |
| 2019 | Nostalgin: Extracting 3D City Models from Historical Image Data. Amol Kapoor, Hunter Larco, Raimondas Kiveris |
| 2019 | OAG: Toward Linking Large-scale Heterogeneous Entity Graphs. Fanjin Zhang, Xiao Liu, Jie Tang, Yuxiao Dong, Peiran Yao, Jie Zhang, Xiaotao Gu, Yan Wang, Bin Shao, Rui Li, Kuansan Wang |
| 2019 | OBOE: Collaborative Filtering for AutoML Model Selection. Chengrun Yang, Yuji Akimoto, Dae Won Kim, Madeleine Udell |
| 2019 | OCC: A Smart Reply System for Efficient In-App Communications. Yue Weng, Huaixiu Zheng, Franziska Bell, Gökhan Tür |
| 2019 | Off-policy Learning for Multiple Loggers. Li He, Long Xia, Wei Zeng, Zhi-Ming Ma, Yihong Zhao, Dawei Yin |
| 2019 | On Dynamic Network Models and Application to Causal Impact. Yu-Chia Chen, Avleen S. Bijral, Juan M. Lavista Ferres |
| 2019 | Online Amnestic DTW to allow Real-Time Golden Batch Monitoring. Chin-Chia Michael Yeh, Yan Zhu, Hoang Anh Dau, Amirali Darvishzadeh, Mikhail Noskov, Eamonn J. Keogh |
| 2019 | Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics. Chao Huang, Xian Wu, Xuchao Zhang, Chuxu Zhang, Jiashu Zhao, Dawei Yin, Nitesh V. Chawla |
| 2019 | Optimizing Impression Counts for Outdoor Advertising. Yipeng Zhang, Yuchen Li, Zhifeng Bao, Songsong Mo, Ping Zhang |
| 2019 | Optimizing Peer Learning in Online Groups with Affinities. Mohammadreza Esfandiari, Dong Wei, Sihem Amer-Yahia, Senjuti Basu Roy |
| 2019 | Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching. Yao Zhou, Fenglong Ma, Jing Gao, Jingrui He |
| 2019 | Optuna: A Next-generation Hyperparameter Optimization Framework. Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, Masanori Koyama |
| 2019 | Origin-Destination Matrix Prediction via Graph Convolution: a New Perspective of Passenger Demand Modeling. Yuandong Wang, Hongzhi Yin, Hongxu Chen, Tianyu Wo, Jie Xu, Kai Zheng |
| 2019 | POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion. Wen Chen, Pipei Huang, Jiaming Xu, Xin Guo, Cheng Guo, Fei Sun, Chao Li, Andreas Pfadler, Huan Zhao, Binqiang Zhao |
| 2019 | Pairwise Comparisons with Flexible Time-Dynamics. Lucas Maystre, Victor Kristof, Matthias Grossglauser |
| 2019 | Paper Matching with Local Fairness Constraints. Ari Kobren, Barna Saha, Andrew McCallum |
| 2019 | PerDREP: Personalized Drug Effectiveness Prediction from Longitudinal Observational Data. Sanjoy Dey, Ping Zhang, Daby Sow, Kenney Ng |
| 2019 | Personalized Attraction Enhanced Sponsored Search with Multi-task Learning. Wei Zhao, Boxuan Zhang, Beidou Wang, Ziyu Guan, Wanxian Guan, Guang Qiu, Wei Ning, Jiming Chen, Hongmin Liu |
| 2019 | Personalized Purchase Prediction of Market Baskets with Wasserstein-Based Sequence Matching. Mathias Kraus, Stefan Feuerriegel |
| 2019 | PinText: A Multitask Text Embedding System in Pinterest. Jinfeng Zhuang, Yu Liu |
| 2019 | Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction. Qi Pi, Weijie Bian, Guorui Zhou, Xiaoqiang Zhu, Kun Gai |
| 2019 | Precipitation Nowcasting with Satellite Imagery. Vadim Lebedev, Vladimir Ivashkin, Irina Rudenko, Alexander Ganshin, Alexander Molchanov, Sergey Ovcharenko, Ruslan Grokhovetskiy, Ivan Bushmarinov, Dmitry Solomentsev |
| 2019 | Predicting Different Types of Conversions with Multi-Task Learning in Online Advertising. Junwei Pan, Yizhi Mao, Alfonso Lobos Ruiz, Yu Sun, Aaron Flores |
| 2019 | Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks. Srijan Kumar, Xikun Zhang, Jure Leskovec |
| 2019 | Predicting Economic Development using Geolocated Wikipedia Articles. Evan Sheehan, Chenlin Meng, Matthew Tan, Burak Uzkent, Neal Jean, Marshall Burke, David B. Lobell, Stefano Ermon |
| 2019 | Predicting Evacuation Decisions using Representations of Individuals' Pre-Disaster Web Search Behavior. Takahiro Yabe, Kota Tsubouchi, Toru Shimizu, Yoshihide Sekimoto, Satish V. Ukkusuri |
| 2019 | Predicting Path Failure In Time-Evolving Graphs. Jia Li, Zhichao Han, Hong Cheng, Jiao Su, Pengyun Wang, Jianfeng Zhang, Lujia Pan |
| 2019 | PressLight: Learning Max Pressure Control to Coordinate Traffic Signals in Arterial Network. Hua Wei, Chacha Chen, Guanjie Zheng, Kan Wu, Vikash V. Gayah, Kai Xu, Zhenhui Li |
| 2019 | Preventing Rhino Poaching through Machine Learning. Olga Liakhovich, Gabriel Domínguez-Conde |
| 2019 | PrivPy: General and Scalable Privacy-Preserving Data Mining. Yi Li, Wei Xu |
| 2019 | ProGAN: Network Embedding via Proximity Generative Adversarial Network. Hongchang Gao, Jian Pei, Heng Huang |
| 2019 | Probabilistic Latent Variable Modeling for Assessing Behavioral Influences on Well-Being. Ehimwenma Nosakhare, Rosalind W. Picard |
| 2019 | Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019. Ankur Teredesai, Vipin Kumar, Ying Li, Rómer Rosales, Evimaria Terzi, George Karypis |
| 2019 | Product Ecosystem Optimization at LinkedIn. Rómer Rosales |
| 2019 | Pythia: AI-assisted Code Completion System. Alexey Svyatkovskiy, Ying Zhao, Shengyu Fu, Neel Sundaresan |
| 2019 | Quantifying Long Range Dependence in Language and User Behavior to improve RNNs. Francois Belletti, Minmin Chen, Ed H. Chi |
| 2019 | QuesNet: A Unified Representation for Heterogeneous Test Questions. Yu Yin, Qi Liu, Zhenya Huang, Enhong Chen, Wei Tong, Shijin Wang, Yu Su |
| 2019 | Raise to Speak: An Accurate, Low-power Detector for Activating Voice Assistants on Smartwatches. 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 |
| 2019 | Randomized Experimental Design via Geographic Clustering. David Rolnick, Kevin Aydin, Jean Pouget-Abadie, Shahab Kamali, Vahab S. Mirrokni, Amir Najmi |
| 2019 | Ranking in Genealogy: Search Results Fusion at Ancestry. Peng Jiang, Yingrui Yang, Gann Bierner, Fengjie Alex Li, Ruhan Wang, Azadeh Moghtaderi |
| 2019 | Real-World Product Deployment of Adaptive Push Notification Scheduling on Smartphones. Tadashi Okoshi, Kota Tsubouchi, Hideyuki Tokuda |
| 2019 | Real-time Attention Based Look-alike Model for Recommender System. Yudan Liu, Kaikai Ge, Xu Zhang, Leyu Lin |
| 2019 | Real-time Event Detection on Social Data Streams. Mateusz Fedoryszak, Brent Frederick, Vijay Rajaram, Changtao Zhong |
| 2019 | Real-time On-Device Troubleshooting Recommendation for Smartphones. Keiichi Ochiai, Kohei Senkawa, Naoki Yamamoto, Yuya Tanaka, Yusuke Fukazawa |
| 2019 | Recent Progress in Zeroth Order Optimization and Its Applications to Adversarial Robustness in Data Mining and Machine Learning. Pin-Yu Chen, Sijia Liu |
| 2019 | Recurrent Neural Networks for Stochastic Control in Real-Time Bidding. Nicolas Grislain, Nicolas Perrin, Antoine Thabault |
| 2019 | Regularized Regression for Hierarchical Forecasting Without Unbiasedness Conditions. Souhaib Ben Taieb, Bonsoo Koo |
| 2019 | Reinforcement Learning to Optimize Long-term User Engagement in Recommender Systems. Lixin Zou, Long Xia, Zhuoye Ding, Jiaxing Song, Weidong Liu, Dawei Yin |
| 2019 | Relation Extraction via Domain-aware Transfer Learning. Shimin Di, Yanyan Shen, Lei Chen |
| 2019 | Representation Learning for Attributed Multiplex Heterogeneous Network. Yukuo Cen, Xu Zou, Jianwei Zhang, Hongxia Yang, Jingren Zhou, Jie Tang |
| 2019 | Reserve Price Failure Rate Prediction with Header Bidding in Display Advertising. Achir Kalra, Chong Wang, Cristian Borcea, Yi Chen |
| 2019 | Retaining Privileged Information for Multi-Task Learning. Fengyi Tang, Cao Xiao, Fei Wang, Jiayu Zhou, Li-Wei H. Lehman |
| 2019 | Revisiting kd-tree for Nearest Neighbor Search. Parikshit Ram, Kaushik Sinha |
| 2019 | Riker: Mining Rich Keyword Representations for Interpretable Product Question Answering. Jie Zhao, Ziyu Guan, Huan Sun |
| 2019 | Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network. Ya Su, Youjian Zhao, Chenhao Niu, Rong Liu, Wei Sun, Dan Pei |
| 2019 | Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement. Ming Lin, Xiaomin Song, Qi Qian, Hao Li, Liang Sun, Shenghuo Zhu, Rong Jin |
| 2019 | Robust Graph Convolutional Networks Against Adversarial Attacks. Dingyuan Zhu, Ziwei Zhang, Peng Cui, Wenwu Zhu |
| 2019 | Robust Task Grouping with Representative Tasks for Clustered Multi-Task Learning. Yaqiang Yao, Jie Cao, Huanhuan Chen |
| 2019 | Roll of Unified Graph Analysis Platforms. Yinglong Xia |
| 2019 | SMOILE: A Shopper Marketing Optimization and Inverse Learning Engine. Abhilash Reddy Chenreddy, Parshan Pakiman, Selvaprabu Nadarajah, Ranganathan Chandrasekaran, Rick Abens |
| 2019 | SPuManTE: Significant Pattern Mining with Unconditional Testing. Leonardo Pellegrina, Matteo Riondato, Fabio Vandin |
| 2019 | Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points. Zhibin Li, Jian Zhang, Qiang Wu, Yongshun Gong, Jinfeng Yi, Christina Kirsch |
| 2019 | Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding. Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia, Charu C. Aggarwal |
| 2019 | Scalable Graph Embeddings via Sparse Transpose Proximities. Yuan Yin, Zhewei Wei |
| 2019 | Scalable Hierarchical Clustering with Tree Grafting. Nicholas Monath, Ari Kobren, Akshay Krishnamurthy, Michael R. Glass, Andrew McCallum |
| 2019 | Scaling Multi-Armed Bandit Algorithms. Edouard Fouché, Junpei Komiyama, Klemens Böhm |
| 2019 | Scaling Multinomial Logistic Regression via Hybrid Parallelism. Parameswaran Raman, Sriram Srinivasan, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan |
| 2019 | Seasonal-adjustment Based Feature Selection Method for Predicting Epidemic with Large-scale Search Engine Logs. Thien Q. Tran, Jun Sakuma |
| 2019 | Seeker: Real-Time Interactive Search. Ari Biswas, Thai T. Pham, Michael Vogelsong, Benjamin Snyder, Houssam Nassif |
| 2019 | Semantic Product Search. Priyanka Nigam, Yiwei Song, Vijai Mohan, Vihan Lakshman, Weitian Allen Ding, Ankit Shingavi, Choon Hui Teo, Hao Gu, Bing Yin |
| 2019 | Separated Trust Regions Policy Optimization Method. Luobao Zou, Zhiwei Zhuang, Yin Cheng, Xuechun Wang, Weidong Zhang |
| 2019 | Sequence Multi-task Learning to Forecast Mental Wellbeing from Sparse Self-reported Data. Dimitris Spathis, Sandra Servia Rodríguez, Katayoun Farrahi, Cecilia Mascolo, Jason Rentfrow |
| 2019 | Sequential Anomaly Detection using Inverse Reinforcement Learning. Min-hwan Oh, Garud Iyengar |
| 2019 | Sequential Scenario-Specific Meta Learner for Online Recommendation. Zhengxiao Du, Xiaowei Wang, Hongxia Yang, Jingren Zhou, Jie Tang |
| 2019 | Sets2Sets: Learning from Sequential Sets with Neural Networks. Haoji Hu, Xiangnan He |
| 2019 | Seven Years of Data Science at Airbnb. Elena Grewal |
| 2019 | Sherlock: A Deep Learning Approach to Semantic Data Type Detection. Madelon Hulsebos, Kevin Zeng Hu, Michiel A. Bakker, Emanuel Zgraggen, Arvind Satyanarayan, Tim Kraska, Çagatay Demiralp, César A. Hidalgo |
| 2019 | Short and Long-term Pattern Discovery Over Large-Scale Geo-Spatiotemporal Data. Sobhan Moosavi, Mohammad Hossein Samavatian, Arnab Nandi, Srinivasan Parthasarathy, Rajiv Ramnath |
| 2019 | Shrinkage Estimators in Online Experiments. Drew Dimmery, Eytan Bakshy, Jasjeet S. Sekhon |
| 2019 | Significance of Patterns in Data Visualisations. Rafael Savvides, Andreas Henelius, Emilia Oikarinen, Kai Puolamäki |
| 2019 | Smart Roles: Inferring Professional Roles in Email Networks. Di Jin, Mark Heimann, Tara Safavi, Mengdi Wang, Wei Lee, Lindsay Snider, Danai Koutra |
| 2019 | Social Recommendation with Optimal Limited Attention. Xin Wang, Wenwu Zhu, Chenghao Liu |
| 2019 | Social Skill Validation at LinkedIn. Xiao Yan, Jaewon Yang, Mikhail Obukhov, Lin Zhu, Joey Bai, Shiqi Wu, Qi He |
| 2019 | Social User Interest Mining: Methods and Applications. Fattane Zarrinkalam, Hossein Fani, Ebrahim Bagheri |
| 2019 | Spatio-temporal Event Forecasting and Precursor Identification. Yue Ning, Liang Zhao, Feng Chen, Chang-Tien Lu, Huzefa Rangwala |
| 2019 | Spinning the AI Pinwheel. Jairam Ranganathan |
| 2019 | Stability and Generalization of Graph Convolutional Neural Networks. Saurabh Verma, Zhi-Li Zhang |
| 2019 | State-Sharing Sparse Hidden Markov Models for Personalized Sequences. Hongzhi Shi, Chao Zhang, Quanming Yao, Yong Li, Funing Sun, Depeng Jin |
| 2019 | Statistical Mechanics Methods for Discovering Knowledge from Modern Production Quality Neural Networks. Charles H. Martin, Michael W. Mahoney |
| 2019 | Streaming Adaptation of Deep Forecasting Models using Adaptive Recurrent Units. Prathamesh Deshpande, Sunita Sarawagi |
| 2019 | Streaming Session-based Recommendation. Lei Guo, Hongzhi Yin, Qinyong Wang, Tong Chen, Alexander Zhou, Nguyen Quoc Viet Hung |
| 2019 | Structured Noise Detection: Application on Well Test Pressure Derivative Data. Farhan Asif Chowdhury, Satomi Suzuki, Abdullah Mueen |
| 2019 | SurfCon: Synonym Discovery on Privacy-Aware Clinical Data. Zhen Wang, Xiang Yue, Soheil Moosavinasab, Yungui Huang, Simon M. Lin, Huan Sun |
| 2019 | TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank. Rama Kumar Pasumarthi, Sebastian Bruch, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork, Jan Pfeifer, Nadav Golbandi, Rohan Anil, Stephan Wolf |
| 2019 | TUBE: Embedding Behavior Outcomes for Predicting Success. Daheng Wang, Tianwen Jiang, Nitesh V. Chawla, Meng Jiang |
| 2019 | TV Advertisement Scheduling by Learning Expert Intentions. Yasuhisa Suzuki, Wemer M. Wee, Itaru Nishioka |
| 2019 | Tackle Balancing Constraint for Incremental Semi-Supervised Support Vector Learning. Shuyang Yu, Bin Gu, Kunpeng Ning, Haiyan Chen, Jian Pei, Heng Huang |
| 2019 | Task-Adversarial Co-Generative Nets. Pei Yang, Qi Tan, Hanghang Tong, Jingrui He |
| 2019 | Temporal Probabilistic Profiles for Sepsis Prediction in the ICU. Eitam Sheetrit, Nir Nissim, Denis Klimov, Yuval Shahar |
| 2019 | Tensorized Determinantal Point Processes for Recommendation. Romain Warlop, Jérémie Mary, Mike Gartrell |
| 2019 | Testing Dynamic Incentive Compatibility in Display Ad Auctions. Yuan Deng, Sébastien Lahaie |
| 2019 | The Error is the Feature: How to Forecast Lightning using a Model Prediction Error. Christian Schön, Jens Dittrich, Richard Müller |
| 2019 | The Identification and Estimation of Direct and Indirect Effects in A/B Tests through Causal Mediation Analysis. Xuan Yin, Liangjie Hong |
| 2019 | The Impact of Person-Organization Fit on Talent Management: A Structure-Aware Convolutional Neural Network Approach. Ying Sun, Fuzhen Zhuang, Hengshu Zhu, Xin Song, Qing He, Hui Xiong |
| 2019 | The Role of: A Novel Scientific Knowledge Graph Representation and Construction Model. Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, Meng Jiang |
| 2019 | The Secret Lives of Names?: Name Embeddings from Social Media. Junting Ye, Steven Skiena |
| 2019 | The Unreasonable Effectiveness, and Difficulty, of Data in Healthcare. Peter Lee |
| 2019 | Three-Dimensional Stable Matching Problem for Spatial Crowdsourcing Platforms. Boyang Li, Yurong Cheng, Ye Yuan, Guoren Wang, Lei Chen |
| 2019 | Time Critic Policy Gradient Methods for Traffic Signal Control in Complex and Congested Scenarios. Stefano Giovanni Rizzo, Giovanna Vantini, Sanjay Chawla |
| 2019 | Time-Series Anomaly Detection Service at Microsoft. Hansheng Ren, Bixiong Xu, Yujing Wang, Chao Yi, Congrui Huang, Xiaoyu Kou, Tony Xing, Mao Yang, Jie Tong, Qi Zhang |
| 2019 | Topic-Enhanced Memory Networks for Personalised Point-of-Interest Recommendation. Xiao Zhou, Cecilia Mascolo, Zhongxiang Zhao |
| 2019 | Towards Identifying Impacted Users in Cellular Services. Shobha Venkataraman, Jia Wang |
| 2019 | Towards Knowledge-Based Personalized Product Description Generation in E-commerce. Qibin Chen, Junyang Lin, Yichang Zhang, Hongxia Yang, Jingren Zhou, Jie Tang |
| 2019 | Towards ML Engineering with TensorFlow Extended (TFX). Konstantinos Katsiapis, Kevin Haas |
| 2019 | Towards Robust and Discriminative Sequential Data Learning: When and How to Perform Adversarial Training? Xiaowei Jia, Sheng Li, Handong Zhao, Sungchul Kim, Vipin Kumar |
| 2019 | Towards Sustainable Dairy Management - A Machine Learning Enhanced Method for Estrus Detection. Kevin Fauvel, Véronique Masson, Élisa Fromont, Philippe Faverdin, Alexandre Termier |
| 2019 | Training and Meta-Training Binary Neural Networks with Quantum Computing. Abdulah Fawaz, Paul Klein, Sebastien Piat, Simone Severini, Peter Mountney |
| 2019 | TrajGuard: A Comprehensive Trajectory Copyright Protection Scheme. Zheyi Pan, Jie Bao, Weinan Zhang, Yong Yu, Yu Zheng |
| 2019 | Transportation: A Data Driven Approach. Jieping Ye |
| 2019 | Tutorial: Are You My Neighbor?: Bringing Order to Neighbor Computing Problems. David C. Anastasiu, Huzefa Rangwala, Andrea Tagarelli |
| 2019 | Tutorial: Data Mining Methods for Drug Discovery and Development. Cao Xiao, Jimeng Sun |
| 2019 | Two-Sided Fairness for Repeated Matchings in Two-Sided Markets: A Case Study of a Ride-Hailing Platform. Tom Sühr, Asia J. Biega, Meike Zehlike, Krishna P. Gummadi, Abhijnan Chakraborty |
| 2019 | Uncovering Pattern Formation of Information Flow. Chengxi Zang, Peng Cui, Chaoming Song, Wenwu Zhu, Fei Wang |
| 2019 | Uncovering the Co-driven Mechanism of Social and Content Links in User Churn Phenomena. Yunfei Lu, Linyun Yu, Peng Cui, Chengxi Zang, Renzhe Xu, Yihao Liu, Lei Li, Wenwu Zhu |
| 2019 | Understanding Consumer Journey using Attention based Recurrent Neural Networks. Yichao Zhou, Shaunak Mishra, Jelena Gligorijevic, Tarun Bhatia, Narayan Bhamidipati |
| 2019 | Understanding the Role of Style in E-commerce Shopping. Hao Jiang, Aakash Sabharwal, Adam Henderson, Diane Hu, Liangjie Hong |
| 2019 | Unifying Inter-region Autocorrelation and Intra-region Structures for Spatial Embedding via Collective Adversarial Learning. Yunchao Zhang, Yanjie Fu, Pengyang Wang, Xiaolin Li, Yu Zheng |
| 2019 | Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts. Junheng Hao, Muhao Chen, Wenchao Yu, Yizhou Sun, Wei Wang |
| 2019 | Unsupervised Clinical Language Translation. Wei-Hung Weng, Yu-An Chung, Peter Szolovits |
| 2019 | Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning. Zheyi Pan, Yuxuan Liang, Weifeng Wang, Yong Yu, Yu Zheng, Junbo Zhang |
| 2019 | UrbanFM: Inferring Fine-Grained Urban Flows. Yuxuan Liang, Kun Ouyang, Lin Jing, Sijie Ruan, Ye Liu, Junbo Zhang, David S. Rosenblum, Yu Zheng |
| 2019 | Using Twitter to Predict When Vulnerabilities will be Exploited. Haipeng Chen, Rui Liu, Noseong Park, V. S. Subrahmanian |
| 2019 | Welfare Maximization in Online Two-sided Marketplaces. Sreenivas Gollapudi |
| 2019 | Whole Page Optimization with Global Constraints. Weicong Ding, Dinesh Govindaraj, S. V. N. Vishwanathan |
| 2019 | dEFEND: Explainable Fake News Detection. Kai Shu, Limeng Cui, Suhang Wang, Dongwon Lee, Huan Liu |
| 2019 | λOpt: Learn to Regularize Recommender Models in Finer Levels. Yihong Chen, Bei Chen, Xiangnan He, Chen Gao, Yong Li, Jian-Guang Lou, Yue Wang |