KDD 2017
August 15, 2017 August 17, 2017

Microsoft Research @ KDD 2017

Location: Halifax, Nova Scotia, Canada

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Accepted papers

Discrete Content-aware Matrix Factorization (opens in new tab)
Defu Lian, University of Electronic Science and Technology of China; Rui Liu, University of Electronic Science and Technology of China; Yong Ge, University of Arizona; Kai Zheng, University of Queensland; Xing Xie, Microsoft Research; Longbing Cao, University of Technology Sydney

A Century of Science: Globalization of Scientific Collaborations, Citations, and Innovations (opens in new tab)
Yuxiao Dong, University of Notre Dame; Hao Ma, Microsoft Research; Zhihong Shen, Microsoft Research; Kuansan Wang, Microsoft Research

Deep Embedding Forest: Forest-based Serving with Deep Embedding Features (opens in new tab)
Jie Zhu, Microsoft; Ying Shan, Microsoft; Jc Mao, Microsoft; Dong Yu, Microsoft; Holakou Rahmanian, University of California Santa Cruz; Yi Zhang, Microsoft

A Dirty Dozen: Twelve Common Metric Interpretation Pitfalls in Online Controlled Experiments (opens in new tab)
Somit Gupta, Microsoft; Pavel Dmitriev, Microsoft; Garnet Vaz, Microsoft; Dong Woo Kim, Microsoft

Planning Bike Lanes based on Sharing-Bikes’ Trajectories (opens in new tab)
Jie Bao, Microsoft Research; Tianfu He, Harbin Institution of Technology; Sijie Ruan, Xidian University; Yanhua Li, Worcester Polytechnic Institute; Yu Zheng, Microsoft Research

Posters

Mixture Factorized Ornstein-Uhlenbeck Processes for Time-Series Forecasting (opens in new tab)
Guo-Jun Qi (UCF); Jiliang Tang (MSU); Jingdong Wang (Microsoft); Jiebo Luo (University of Rochester)

ReasoNet: Learning to Stop Reading in Machine Comprehension (opens in new tab)
Yelong Shen, Microsoft Research; Po-Sen Huang, Microsoft Research; Jianfeng Gao, Microsoft Research; Weizhu Chen, Microsoft Research

DeepProbe: Information Directed Sequence Understanding via Recurrent Neural Networks (opens in new tab)
Zi Yin, Stanford University; Keng-Hao Chang, Microsoft; Ruofei Zhang, Stanford University

Discovering Concepts Using Large Table Corpus (opens in new tab)
Keqian Li, University of California, Santa Barbara; Yeye He, Microsoft Research; Kris Ganjam, Microsoft Research