大会 | NIPS 2017录用结果全公布，清华北大10篇，BAT 4篇（附详细名单）

AI科技评论按：NIPS 2017 将于 12 月份在美国长滩举行，本届NIPS共收到 3240 篇论文投稿，录用 678 篇，录用率为 20.9%；其中包括 40 篇口头报告论文和 112 篇 spotlight 论文。详细录用名单日前已经公布，可参见：https://nips.cc/Conferences/2017/AcceptedPapersInitial

为方便浏览全貌，AI科技评论为读者整理了多家高校及企业的录用名单。

先来看看国内高校情况。国人心目中科研实力最强的清华大学，今年共有6篇录用论文，包括张钹院士、王建民博士、鲁继文博士、朱军博士都有论文被录用；而北京大学也表现不俗，有四篇论文被录用。此外，包括中国科学院、中国科学技术大学、香港科技大学、香港中文大学及香港城市大学在内的多家高校也有多篇论文中了NIPS。由于论文可能涉及多位合作者，因此以下的名单均以第一作者所属机构为准。

清华大学

• PredRNN: Recurrent Neural Networks for Video Prediction using Spatiotemporal LSTMs

  Yunbo Wang (Tsinghua University) · Mingsheng Long (Tsinghua University) · Jianmin Wang (Tsinghua University) · Philip S Yu (UIC)

• Learning Multiple Tasks with Deep Relationship Networks

  Mingsheng Long (Tsinghua University) · Jianmin Wang (Tsinghua University) · Philip S Yu (UIC)

• Runtime Neural Pruning

  Ji Lin (Tsinghua University) · Yongming Rao (Tsinghua University) · Jiwen Lu (Tsinghua University)

• Triple Generative Adversarial Nets

  Chongxuan LI (Tsinghua University) · Kun Xu () · Jun Zhu (Tsinghua University) · Bo Zhang (Tsinghua University)

• Accelerated Stochastic Greedy Coordinate Descent by Soft Thresholding Projection onto Simplex

  Chaobing Song (Tsinghua University) · Shaobo Cui (Tsinghua University) · Shu-Tao Xia (Tsinghua University) · Yong Jiang (Tsinghua-Berkeley Shenzhen Institute)

• Population Matching Discrepancy and Applications in Deep Learning

  Jianfei Chen (Tsinghua University) · Chongxuan LI (Tsinghua University) · Yizhong Ru (Tsinghua University) · Jun Zhu (Tsinghua University)

北京大学

• Deep Dynamic Poisson Factorization Model

  Chengyue Gong (PeKing University) • win-bin huang (peking university)

• Faster and Non-ergodic O(1/K) Stochastic Alternating Direction Method of Multipliers

  Cong Fang (Peking University) · Feng Cheng (Peking University) · Zhouchen Lin (Peking University)

• From Bayesian Sparsity to Gated Recurrent Nets

  Hao He (PekingUniversity) · Bo Xin (Microsoft Research) · David Wipf (Microsoft Research)

• The Expressive Power of Neural Networks: A View from the Width

  Zhou Lu (Peking University) · Hongming Pu (Peking university) · Feicheng Wang (Peking University) · Zhiqiang Hu (Peking University) · Liwei Wang (Peking University)

中国科学院

• Deep supervised discrete hashing

  Qi Li (Institute of Automation, Chinese Academy of Sciences) · Zhenan Sun () · Ran He (CASIA) · Tieniu Tan (Chinese Academy of Sciences)

中国科学技术大学

• Deliberation Networks: Sequence Generation Beyond One-Pass Decoding

  Yingce Xia (University of Science and Technology of China) · Lijun Wu (Sun Yat-sen University) · Jianxin Lin (USTC) · Fei Tian (Miicrosoft Research) · Tao Qin (Microsoft Research) · Tie-Yan Liu (Microsoft Research)

• Subset Selection under Noise

  Chao Qian (University of Science and Technology of China) · Jing-Cheng Shi (Nanjing University) · Yang Yu () · Ke Tang (University of Science and Technology of China) · Zhi-Hua Zhou (Nanjing University)

香港中文大学

• Rethinking Feature Discrimination and Polymerization for Large-scale Recognition

  Yu Liu (The Chinese University of Hong Kong) · Hongyang Li (The Chinese University of Hong Kong) · Xiaogang Wang (The Chinese University of Hong Kong)

• Contrastive Learning for Image Captioning

  Bo Dai (The Chinese University of Hong Kong) · Dahua Lin (The Chinese University of Hong Kong)

• Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds

  Yuanyuan Liu (The Chinese University of Hong Kong) · Fanhua Shang (The Chinese University of Hong Kong) · James Cheng (The Chinese University of Hong Kong) · Hong Cheng (The Chinese University of Hong Kong) · Licheng Jiao (Xidian University)

• Geometric Descent Method for Convex Composite Minimization

  Shixiang Chen (The Chinese University of HongKong) · Shiqian Ma (UC Davis) · Wei Liu (Tencent Technology (Shenzhen) Company Limited)

香港城市大学

• Incorporating Side Information by Adaptive Convolution

  Di Kang (City University of Hong Kong) · Debarun Dhar (City University of Hong Kong) · Antoni Chan (City University of Hong Kong)

香港科技大学

• Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model

  Xingjian Shi (HKUST) · Hao Wang (HKUST) · Zhihan Gao (HKUST) · Leonard Lausen (HKUST) · Dit-Yan Yeung (HKUST, Hong Kong) · Wang-chun WOO (HKO) · Wai-kin Wong (HKO)

自 1987 年到 2000 年，NIPS都在美国丹佛举办，虽然后来也曾经在加拿大温哥华、西班牙的格兰纳达、加拿大蒙特利尔举办，但不得不承认的是，美国一直是全球科研的主要阵地。今年NIPS上，美国计算机四大名校（CMU、MIT、UC伯克利、斯坦福）“理所当然”地霸屏，仅以第一作者所属机构统计的录用论文就达92篇（有一篇是第一作者隶属双院校的），其中 CMU 37篇，成为今年最大赢家；MIT和斯坦福各有20篇论文，UC伯克利有16篇论文被录用。

由于正文篇幅有限，关注“AI科技评论”（aitechtalk）后，回复“美国名校NIPS”可查看四大名校论文完整名单。

再和AI科技评论一起来看看国内BAT三家的论文录用情况。今年NIPS上，尚未看到阿里被录用的论文，腾讯有一篇作为第一作者的录用论文，另有两篇为合作论文；而百度美研院今年有一篇关于Deep Voice2的论文被收录；截至目前，尚未看到阿里的相关录用论文。

腾讯

• Mixture-Rank Matrix Approximation for Collaborative Filtering

  Dongsheng Li (IBM Research - China) · Chao Chen (Tongji University) · Wei Liu (Tencent Technology (Shenzhen) Company Limited) · Tun Lu (Fudan University) · Ning Gu (Fudan University) · Stephen Chu (IBM Research - China)

• Geometric Descent Method for Convex Composite Minimization

  Shixiang Chen (The Chinese University of HongKong) · Shiqian Ma (UC Davis) · Wei Liu (Tencent Technology (Shenzhen) Company Limited)

• Efficient Optimization for Linear Dynamical Systems with Applications to Clustering and Sparse Coding

  Wenbing Huang (Tencent AI Lab) · Fuchun Sun (Tsinghua University) · Tong Zhang (The Australian National University) · Junzhou Huang (University of Texas at Arlington) · Mehrtash Harandi (Data61)

百度研究院

• Deep Voice 2: Multi-Speaker Neural Text-to-Speech

  Andrew Gibiansky (Baidu Research)

最后再看看其它国际研究院/企业的表现。惊喜之外意料之中的是，微软研究院共有16篇第一作者论文被录用，包括此前AI科技评论报道提及的，微软亚洲研究院的4篇文章。谷歌今年有7篇论文上榜，OpenAI，Facebook也表现不俗。

往期报道可参阅：

速报 | 刚刚，NIPS 2017 结果出炉，默默看各路大神公布喜讯

微软研究院

• Decoding with Value Networks for Neural Machine Translation

  Di He (Microsoft Research) · Hanqing Lu (Zhejiang University) · Yingce Xia (University of Science and Technology of China) · Tao Qin (Microsoft Research) · Liwei Wang (Peking University) · Tieyan Liu (Microsoft Research)

• Inference in Graphical Models via Semidefinite Programming Hierarchies

  Murat Erdogdu (Microsoft Research) · Yash Deshpande (MIT) · Andrea Montanari (Stanford)

• Neural Program Meta-Induction

  Jacob Devlin (Microsoft Research) · Rudy R Bunel (Oxford University) · Rishabh Singh (Microsoft Research) · Matthew Hausknecht (Microsoft Research) · Pushmeet Kohli (DeepMind)

• Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM

  Steven Wu (Microsoft Research) · Bo Waggoner () · Seth Neel (University of Pennsylvania) · Aaron Roth (University of Pennsylvania) · Katrina Ligett ()

• A Highly Efficient Gradient Boosting Decision Tree

  Guolin Ke (Microsoft Research) · Qi Meng (Peking University) · Taifeng Wang (Microsoft Research) · Wei Chen (Microsoft Research Asia) · Weidong Ma (Microsoft Research) · Tie-Yan Liu (Microsoft Research)

• Clustering Billions of Reads for DNA Data Storage

  Cyrus Rashtchian (University of Washington) · Konstantin Makarychev (Microsoft) · Luis Ceze (Microsoft) · Karin Strauss (Microsoft Research) · Sergey Yekhanin (Microsoft) · Djordje Jevdjic (Microsoft Research) · Miklos Racz (Princeton University) · Siena Ang (Microsoft)

• Collecting Telemetry Data Privately

  Bolin Ding (Microsoft) · Janardhan Kulkarni (Microsoft Research) · Sergey Yekhanin (Microsoft)

• Off-policy evaluation for slate recommendation

  Adith Swaminathan (Microsoft Research) · Akshay Krishnamurthy () · Alekh Agarwal (Microsoft Research) · Miro Dudik (Microsoft Research) · John Langford (Microsoft Research) · Damien Jose (Microsoft) · Imed Zitouni (Microsoft)

• A Decomposition of Forecast Error in Prediction Markets

  Miro Dudik (Microsoft Research) · Sebastien Lahaie (Google) · Ryan M Rogers (University of Pennsylvania) · Jennifer Wortman Vaughan (Microsoft Research)

• Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation

  Christian Borgs (Microsoft Research New England) · Jennifer Chayes (Microsoft Research) · Christina Lee (MIT) · Devavrat Shah (Massachusetts Institute of Technology)

• Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes

  Jianshu Chen (Microsoft Research, Redmond, W) · Chong Wang () · Lin Xiao (Microsoft Research) · Ji He (University Washington) · Lihong Li (Microsoft Research) · Li Deng (Citadel)

• Online Learning with a Hint

  Ofer Dekel (Microsoft Research) · arthur flajolet (MIT) · Nika Haghtalab (Carnegie Mellon University) · Patrick Jaillet (Massachusetts Institute of Technology)

• A Sample Complexity Measure with Applications to Learning Optimal Auctions

  Vasilis Syrgkanis (Microsoft Research)

• Hybrid Reward Architecture for Reinforcement Learning

  Harm Van Seijen (Microsoft Research) · Romain Laroche () · Mehdi Fatemi () · Joshua Romoff (McGill University)

• Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls

  Zeyuan Allen-Zhu (Microsoft Research) · Elad Hazan (Princeton University) · Wei Hu (Princeton University) · Yuanzhi Li (Princeton University)

• Z-Forcing: Training Stochastic Recurrent Networks

  Marc-Alexandre Côté (Microsoft Maluuba) · Alessandro Sordoni (Microsoft Maluuba) · Anirudh Goyal ALIAS PARTH GOYAL (Université de Montréal) · Nan Ke (MILA, École Polytechnique de Montréal) · Yoshua Bengio (U. Montreal)

谷歌

• On the Consistency of Quick Shift

  Heinrich Jiang (Google)

• Attention is All you Need

  Ashish Vaswani (Google Brain) · Noam Shazeer (Google) · Niki Parmar (Google) · Llion Jones (Google) · Jakob Uszkoreit (Google, Inc.) · Aidan N Gomez (University of Toronto) · Łukasz Kaiser (Google Brain)

  AI科技评论往期报道：

  谷歌推出基于注意机制的全新翻译框架，Attention is All You Need!
  

• Parameter-Free Online Learning via Model Selection

  Dylan J Foster (Cornell University) · Satyen Kale (Google) · Mehryar Mohri (Courant Institute and Google) · Karthik Sridharan (Cornell University)

• SVCCA: Singular Vector Canonical Correlation Analysis for Deep Understanding and Improvement

  Maithra Raghu (Cornell University and Google Brain) · Justin Gilmer (Google Brain) · Jason Yosinski (Uber) · Jascha Sohl-Dickstein (Google Brain)

• Neural Discrete Representation Learning

  Aaron van den Oord (Google Deepmind) · Oriol Vinyals (Google DeepMind) · koray kavukcuoglu (DeepMind)

• Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

  Balaji Lakshminarayanan (Google Deepmind) · Alexander Pritzel (Google Deepmind) · Charles Blundell (DeepMind)

• Acceleration and Averaging in Stochastic Descent Dynamics

  Walid Krichene (Google)

OpenAI

• Deep Reinforcement Learning from Human Preferences

  Paul F Christiano (OpenAI) · Jan Leike (DeepMind) · Tom Brown (OpenAI) · Miljan Martic (DeepMind) · Shane Legg (DeepMind) · Dario Amodei (OpenAI)

• Hindsight Experience Replay

  Marcin Andrychowicz (OpenAI) · Filip Wolski (OpenAI) · Alex Ray (OpenAI) · Jonas Schneider (OpenAI) · Rachel Fong (OpenAI) · Peter Welinder (OpenAI) · Bob McGrew (OpenAI) · Josh Tobin (OpenAI) · OpenAI Pieter Abbeel (OpenAI, UC Berkeley) · Wojciech Zaremba (OpenAI)

• Hierarchical Implicit Models and Likelihood-Free Variational Inference

  Dustin Tran (Columbia University & OpenAI) · Rajesh Ranganath (Princeton University) · David Blei (Columbia University)

Facebook

• ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games

  Yuandong Tian (Facebook AI Research) · Qucheng Gong (Facebook AI Research) · Wenling Shang (435024885627) · Yuxin Wu (Facebook AI Research) · C. Lawrence Zitnick (Facebook AI Research)

  AI科技评论往期报道：

  详解Facebook田渊栋NIPS2017论文：让大家都能做得起深度强化学习研究的ELF平台
  

• Multi-agent Predictive Modeling with Attentional CommNets

  Yedid Hoshen (Facebook AI Research)

• Fader Networks: Generating Image Variations by Sliding Attribute Values

  Guillaume Lample (Facebook AI Research) · Neil Zeghidour (Facebook A.I. Research / Ecole Normale Supérieure) · Nicolas Usunier (Facebook AI Research) · Antoine Bordes (Facebook AI Research) · Ludovic DENOYER (Universite Pierre et Marie Curie - Paris) · Marc'Aurelio Ranzato (Facebook)

• Poincaré Embeddings for Learning Hierarchical Representations

  Maximillian Nickel (Facebook) · Douwe Kiela (Facebook AI Research)

• Gradient Episodic Memory for Continuum Learning

  David Lopez-Paz (Facebook AI Research) · Marc'Aurelio Ranzato (Facebook)

• Houdini: Democratizing Adversarial Examples

  Moustapha Cisse (Facebook AI Research) · Yossi Adi (Bar Ilan University) · Natalia Neverova (Facebook AI Research) · Joseph Keshet (Bar-Ilan University)

更多资讯敬请关注AI科技评论。

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第五届CCF大数据学术会议将于2017年10月13日-15日在深圳举行，雷锋网作为协办单位将进行全程报道。本次会议邀请到包括何友院士、Philip S. Yu、Usama Fayyad、Yi Pan、芮勇等多位知名顶级学者交流大数据研究与应用的成果和经验，共同探讨产业化所面临的关键性挑战问题和研究方向。

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