NIPS-2018最新前沿人工智能论文分享

2018 年 12 月 5 日 深度学习与NLP

NIPS（现称NeurIPS），全称神经信息处理系统大会(Conference and Workshop on Neural Information Processing Systems)，是一个关于机器学习和计算神经科学的国际会议。该会议固定在每年的12月举行,由NIPS基金会主办。NIPS是机器学习领域的顶级会议。在中国计算机学会的国际学术会议排名中，NIPS为人工智能领域的A类会议。

目前，NIPS-2018，即第32届年NIPS会于2018年12月2日至8日在加拿大蒙特利尔会议中心举行。会议流程安排如下：

NIPS-2018主页

https://nips.cc/Conferences/2018/Dates

分享由 S. Bengio、H. Wallach、H. Larochelle和K. Grauman等人整理的NIPS-2018会议的论文列表。

文末附论文完整且带链接版地址。

论文TOP列表

1· Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization Francis Bach

2· Structure-Aware Convolutional Neural Networks Jianlong Chang, Jie Gu, Lingfeng Wang, GAOFENG MENG, SHIMING XIANG, Chunhong Pan

3· Kalman Normalization: Normalizing Internal Representations Across Network Layers Guangrun Wang, jiefeng peng, Ping Luo, Xinjiang Wang, Liang Lin

4· HOGWILD!-Gibbs can be PanAccurate Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti

5· Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language Seonghyeon Nam, Yunji Kim, Seon Joo Kim

6· IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis Huaibo Huang, zhihang li, Ran He, Zhenan Sun, Tieniu Tan

7· Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with \beta-Divergences Jeremias Knoblauch, Jack E. Jewson, Theodoros Damoulas

8· Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning Tyler Scott, Karl Ridgeway, Michael C. Mozer

9· Generalized Inverse Optimization through Online Learning Chaosheng Dong, Yiran Chen, Bo Zeng

10· An Off-policy Policy Gradient Theorem Using Emphatic Weightings Ehsan Imani, Eric Graves, Martha White

11· Supervised autoencoders: Improving generalization performance with unsupervised regularizers Lei Le, Andrew Patterson, Martha White

12· Visual Object Networks: Image Generation with Disentangled 3D Representations Jun-Yan Zhu, Zhoutong Zhang, Chengkai Zhang, Jiajun Wu, Antonio Torralba, Josh Tenenbaum, Bill Freeman

13· Understanding Weight Normalized Deep Neural Networks with Rectified Linear Units Yixi Xu, Xiao Wang

14· Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems Mrinmaya Sachan, Kumar Avinava Dubey, Tom M. Mitchell, Dan Roth, Eric P. Xing

15· Learning long-range spatial dependencies with horizontal gated recurrent units Drew Linsley, Junkyung Kim, Vijay Veerabadran, Charles Windolf, Thomas Serre

16· Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution Zhisheng Zhong, Tiancheng Shen, Yibo Yang, Zhouchen Lin, Chao Zhang

17· Fast Similarity Search via Optimal Sparse Lifting Wenye Li, Jingwei Mao, Yin Zhang, Shuguang Cui

18· Learning Deep Disentangled Embeddings With the F-Statistic Loss Karl Ridgeway, Michael C. Mozer

19· Geometrically Coupled Monte Carlo Sampling Mark Rowland, Krzysztof M. Choromanski, François Chalus, Aldo Pacchiano, Tamas Sarlos, Richard E. Turner, Adrian Weller

20· Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose Estimation Siyuan Huang, Siyuan Qi, Yinxue Xiao, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu

21· An Efficient Pruning Algorithm for Robust Isotonic Regression Cong Han Lim

22· PAC-learning in the presence of adversaries Daniel Cullina, Arjun Nitin Bhagoji, Prateek Mittal

23· Sparse DNNs with Improved Adversarial Robustness Yiwen Guo, Chao Zhang, Changshui Zhang, Yurong Chen

24· Snap ML: A Hierarchical Framework for Machine Learning Celestine Dünner, Thomas Parnell, Dimitrios Sarigiannis, Nikolas Ioannou, Andreea Anghel, Gummadi Ravi, Madhusudanan Kandasamy, Haralampos Pozidis

25· See and Think: Disentangling Semantic Scene Completion Shice Liu, YU HU, Yiming Zeng, Qiankun Tang, Beibei Jin, Yinhe Han, Xiaowei Li

26· Chain of Reasoning for Visual Question Answering Chenfei Wu, Jinlai Liu, Xiaojie Wang, Xuan Dong

27· Sigsoftmax: Reanalysis of the Softmax Bottleneck Sekitoshi Kanai, Yasuhiro Fujiwara, Yuki Yamanaka, Shuichi Adachi

28· Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation Wenqi Ren, Jiawei Zhang, Lin Ma, Jinshan Pan, Xiaochun Cao, Wangmeng Zuo, Wei Liu, Ming-Hsuan Yang

29· Probabilistic Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC Tolga Birdal, Umut Simsekli, Mustafa Onur Eken, Slobodan Ilic

30· MetaAnchor: Learning to Detect Objects with Customized Anchors Tong Yang, Xiangyu Zhang, Zeming Li, Wenqiang Zhang, Jian Sun

31· Image Inpainting via Generative Multi-column Convolutional Neural Networks Yi Wang, Xin Tao, Xiaojuan Qi, Xiaoyong Shen, Jiaya Jia

32· On Misinformation Containment in Online Social Networks Amo Tong, Ding-Zhu Du, Weili Wu

· A^2-Nets: Double Attention Networks Yunpeng Chen, Yannis Kalantidis, Jianshu Li, Shuicheng Yan, Jiashi Feng

33· Self-Supervised Generation of Spatial Audio for 360° Video Pedro Morgado, Nuno Nvasconcelos, Timothy Langlois, Oliver Wang

34· How Many Samples are Needed to Estimate a Convolutional Neural Network? Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan R. Salakhutdinov, Aarti Singh

35· Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced Simon S. Du, Wei Hu, Jason D. Lee

36· Optimization for Approximate Submodularity Yaron Singer, Avinatan Hassidim

37· (Probably) Concave Graph Matching Haggai Maron, Yaron Lipman

38· Deep Defense: Training DNNs with Improved Adversarial Robustness Ziang Yan, Yiwen Guo, Changshui Zhang

39· Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes Junqi Tang, Mohammad Golbabaee, Francis Bach, Mike E. davies

40· Implicit Reparameterization Gradients Mikhail Figurnov, Shakir Mohamed, Andriy Mnih

· Training DNNs with Hybrid Block Floating Point Mario Drumond, Tao LIN, Martin Jaggi, Babak Falsafi

41· A Model for Learned Bloom Filters and Optimizing by Sandwiching Michael Mitzenmacher

42· Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis Haoye Dong, Xiaodan Liang, Ke Gong, Hanjiang Lai, Jia Zhu, Jian Yin

43· Deep Functional Dictionaries: Learning Consistent Semantic Structures on 3D Models from Functions Minhyuk Sung, Hao Su, Ronald Yu, Leonidas J. Guibas

44· Nonlocal Neural Networks, Nonlocal Diffusion and Nonlocal Modeling Yunzhe Tao, Qi Sun, Qiang Du, Wei Liu

45· Are ResNets Provably Better than Linear Predictors? Ohad Shamir

46· Learning to Decompose and Disentangle Representations for Video Prediction Jun-Ting Hsieh, Bingbin Liu, De-An Huang, Li F. Fei-Fei, Juan Carlos Niebles

47· Multi-Task Learning as Multi-Objective Optimization Ozan Sener, Vladlen Koltun

48· Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search Zhuwen Li, Qifeng Chen, Vladlen Koltun

49· Self-Erasing Network for Integral Object Attention Qibin Hou, PengTao Jiang, Yunchao Wei, Ming-Ming Cheng

50· LinkNet: Relational Embedding for Scene Graph Sanghyun Woo, Dahun Kim, Donghyeon Cho, In So Kweon