Microsoft @ NIPS 2017

A Decomposition of Forecast Error in Prediction Markets
Miro Dudik (Microsoft Research), Jennifer Wortman Vaughan (Microsoft Research)

A Highly Efficient Gradient Boosting Decision Tree
Guolin Ke (Microsoft Research), Taifeng Wang (Microsoft Research), Wei Chen (Microsoft Research), Weidong Ma (Microsoft Research), Tie-Yan Liu (Microsoft Research)

A Sample Complexity Measure with Applications to Learning Optimal Auctions
Vasilis Syrgkanis (Microsoft Research)

Adversarial Ranking for Language Generation
Xiaodong He (Microsoft Research), Zhengyou Zhang (Microsoft Research)

Clustering Billions of Reads for DNA Data Storage
Luis Ceze, Karin Strauss (Microsoft Research), Sergey Yekhanin (Microsoft Research), Djordje Jevdjic (Microsoft Research), Siena Ang (Microsoft), Konstantin Makarychev (Microsoft)

Collecting Telemetry Data Privately
Bolin Ding (Microsoft Research), Janardhan Kulkarni (Microsoft Research), Sergey Yekhanin (Microsoft Research)

Communication-Efficient Stochastic Gradient Descent, with Applications to Neural Networks
Ryota Tomioka (Microsoft Research)

Consistent Robust Regression
Prateek Jain (Microsoft Research)

Decoding with Value Networks for Neural Machine Translation
Di He, Tao Qin (Microsoft Research), Tieyan Liu (Microsoft Research)

Deliberation Networks: Sequence Generation Beyond One-Pass Decoding
Jianxin Lin, Fei Tian (Microsoft Research), Tao Qin (Microsoft Research), Tie-Yan Liu (Microsoft Research)

Efficiency Guarantees from Data
Vasilis Syrgkanis (Microsoft Research)

Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach
Hoifung Poon (Microsoft Research), Eric Horvitz (Microsoft Research)

From Bayesian Sparsity to Gated Recurrent Nets
David Wipf (Microsoft Research)

Hybrid Reward Architecture for Reinforcement Learning
Harm Van Seijen (Microsoft Research), Mehdi Fatemi (Microsoft Research)

Identifying Outlier Arms in Multi-Armed Bandit
Chi Wang (Microsoft Research)

Improving Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms and Its Applications
Wei Chen (Microsoft Research)

Influence Maximization with ε-Almost Submodular Threshold Function
Wei Chen (Microsoft Research)

Large-Scale Quadratically Constrained Quadratic Program via Low-Discrepancy Sequences
Kinjal Basu (LinkedIn Corporation), Ankan Saha (LinkedIn Corporation), Shaunak Chatterjee (LinkedIn Corporation)

Learning Mixture of Gaussians with Streaming Data
Prateek Jain (Microsoft Research)

Neural Program Meta-Induction
Jacob Devlin (Microsoft Research), Rishabh Singh (Microsoft Research), Matthew Hausknecht (Microsoft Research)

Off-policy Evaluation for Slate Recommendation
Adith Swaminathan (Microsoft Research), Alekh Agarwal (Microsoft Research), Miro Dudik (Microsoft Research), Damien Jose (Microsoft), Imed Zitouni (Microsoft Research)

Online Learning with a Hint
Ofer Dekel (Microsoft Research)

Plan, Attend, Generate: Planning for Sequence-to-Sequence Models
Adam Trischler (Microsoft)

Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes
Jianshu Chen (Microsoft Research), Lin Xiao (Microsoft Research)

Robust Optimization for Non-Convex Objectives
Vasilis Syrgkanis (Microsoft Research), Brendan Lucier (Microsoft Research)

Stabilizing Training of Generative Adversarial Networks through Regularization
Sebastian Nowozin (Microsoft Research)

Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues
Moshe Babaioff (Microsoft Research)

The Numerics of GANs
Sebastian Nowozin (Microsoft Research)

Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation
Christian Borgs (Microsoft Research), Jennifer Chayes (Microsoft Research)

Unsupervised Sequence Classification using Sequential Output Statistics
Jianshu Chen (Microsoft Research)

Z-Forcing: Training Stochastic Recurrent Networks
Marc-Alexandre Côté (Microsoft Research), Alessandro Sordoni (Microsoft Research, Maluuba)