Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDNeurIPS 2018: Montréal, Canada
- Samy Bengio, Hanna M. Wallach, Hugo Larochelle, Kristen Grauman, Nicolò Cesa-Bianchi, Roman Garnett:
Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada. 2018
- Francis R. Bach:
Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization. 1-10 - Jianlong Chang, Jie Gu, Lingfeng Wang, Gaofeng Meng, Shiming Xiang, Chunhong Pan:
Structure-Aware Convolutional Neural Networks. 11-20 - Guangrun Wang, Jiefeng Peng, Ping Luo, Xinjiang Wang, Liang Lin:
Kalman Normalization: Normalizing Internal Representations Across Network Layers. 21-31 - Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti:
HOGWILD!-Gibbs can be PanAccurate. 32-41 - Seonghyeon Nam, Yunji Kim, Seon Joo Kim:
Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language. 42-51 - Huaibo Huang, Zhihang Li, Ran He, Zhenan Sun, Tieniu Tan:
IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis. 52-63 - Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas:
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with \beta-Divergences. 64-75 - Tyler R. Scott, Karl Ridgeway, Michael C. Mozer:
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning. 76-85 - Chaosheng Dong, Yiran Chen, Bo Zeng:
Generalized Inverse Optimization through Online Learning. 86-95 - Ehsan Imani, Eric Graves, Martha White:
An Off-policy Policy Gradient Theorem Using Emphatic Weightings. 96-106 - Lei Le, Andrew Patterson, Martha White:
Supervised autoencoders: Improving generalization performance with unsupervised regularizers. 107-117 - Jun-Yan Zhu, Zhoutong Zhang, Chengkai Zhang, Jiajun Wu, Antonio Torralba, Josh Tenenbaum, Bill Freeman:
Visual Object Networks: Image Generation with Disentangled 3D Representations. 118-129 - Yixi Xu, Xiao Wang:
Understanding Weight Normalized Deep Neural Networks with Rectified Linear Units. 130-139 - Mrinmaya Sachan, Kumar Avinava Dubey, Tom M. Mitchell, Dan Roth, Eric P. Xing:
Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems. 140-151 - Drew Linsley, Junkyung Kim, Vijay Veerabadran, Charles Windolf, Thomas Serre:
Learning long-range spatial dependencies with horizontal gated recurrent units. 152-164 - Zhisheng Zhong, Tiancheng Shen, Yibo Yang, Zhouchen Lin, Chao Zhang:
Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution. 165-175 - Wenye Li, Jingwei Mao, Yin Zhang, Shuguang Cui:
Fast Similarity Search via Optimal Sparse Lifting. 176-184 - Karl Ridgeway, Michael C. Mozer:
Learning Deep Disentangled Embeddings With the F-Statistic Loss. 185-194 - Mark Rowland, Krzysztof Choromanski, François Chalus, Aldo Pacchiano, Tamás Sarlós, Richard E. Turner, Adrian Weller:
Geometrically Coupled Monte Carlo Sampling. 195-205 - Siyuan Huang, Siyuan Qi, Yinxue Xiao, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu:
Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose Estimation. 206-217 - Cong Han Lim:
An Efficient Pruning Algorithm for Robust Isotonic Regression. 218-227 - Daniel Cullina, Arjun Nitin Bhagoji, Prateek Mittal:
PAC-learning in the presence of adversaries. 228-239 - Yiwen Guo, Chao Zhang, Changshui Zhang, Yurong Chen:
Sparse DNNs with Improved Adversarial Robustness. 240-249 - Celestine Dünner, Thomas P. Parnell, Dimitrios Sarigiannis, Nikolas Ioannou, Andreea Anghel, Gummadi Ravi, Madhusudanan Kandasamy, Haralampos Pozidis:
Snap ML: A Hierarchical Framework for Machine Learning. 250-260 - Shice Liu, Yu Hu, Yiming Zeng, Qiankun Tang, Beibei Jin, Yinhe Han, Xiaowei Li:
See and Think: Disentangling Semantic Scene Completion. 261-272 - Chenfei Wu, Jinlai Liu, Xiaojie Wang, Xuan Dong:
Chain of Reasoning for Visual Question Answering. 273-283 - Sekitoshi Kanai, Yasuhiro Fujiwara, Yuki Yamanaka, Shuichi Adachi:
Sigsoftmax: Reanalysis of the Softmax Bottleneck. 284-294 - Wenqi Ren, Jiawei Zhang, Lin Ma, Jinshan Pan, Xiaochun Cao, Wangmeng Zuo, Wei Liu, Ming-Hsuan Yang:
Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation. 295-305 - Tolga Birdal, Umut Simsekli, Mustafa Onur Eken, Slobodan Ilic:
Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC. 306-317 - Tong Yang, Xiangyu Zhang, Zeming Li, Wenqiang Zhang, Jian Sun:
MetaAnchor: Learning to Detect Objects with Customized Anchors. 318-328 - Yi Wang, Xin Tao, Xiaojuan Qi, Xiaoyong Shen, Jiaya Jia:
Image Inpainting via Generative Multi-column Convolutional Neural Networks. 329-338 - Guangmo Amo Tong, Ding-Zhu Du, Weili Wu:
On Misinformation Containment in Online Social Networks. 339-349 - Yunpeng Chen, Yannis Kalantidis, Jianshu Li, Shuicheng Yan, Jiashi Feng:
A^2-Nets: Double Attention Networks. 350-359 - Pedro Morgado, Nuno Vasconcelos, Timothy R. Langlois, Oliver Wang:
Self-Supervised Generation of Spatial Audio for 360° Video. 360-370 - Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh:
How Many Samples are Needed to Estimate a Convolutional Neural Network? 371-381 - Simon S. Du, Wei Hu, Jason D. Lee:
Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced. 382-393 - Yaron Singer, Avinatan Hassidim:
Optimization for Approximate Submodularity. 394-405 - Haggai Maron, Yaron Lipman:
(Probably) Concave Graph Matching. 406-416 - Ziang Yan, Yiwen Guo, Changshui Zhang:
Deep Defense: Training DNNs with Improved Adversarial Robustness. 417-426 - Junqi Tang, Mohammad Golbabaee, Francis R. Bach, Mike E. Davies:
Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes. 427-438 - Mikhail Figurnov, Shakir Mohamed, Andriy Mnih:
Implicit Reparameterization Gradients. 439-450 - Mario Drumond, Tao Lin, Martin Jaggi, Babak Falsafi:
Training DNNs with Hybrid Block Floating Point. 451-461 - Michael Mitzenmacher:
A Model for Learned Bloom Filters and Optimizing by Sandwiching. 462-471 - Haoye Dong, Xiaodan Liang, Ke Gong, Hanjiang Lai, Jia Zhu, Jian Yin:
Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis. 472-482 - Minhyuk Sung, Hao Su, Ronald Yu, Leonidas J. Guibas:
Deep Functional Dictionaries: Learning Consistent Semantic Structures on 3D Models from Functions. 483-493 - Yunzhe Tao, Qi Sun, Qiang Du, Wei Liu:
Nonlocal Neural Networks, Nonlocal Diffusion and Nonlocal Modeling. 494-504 - Ohad Shamir:
Are ResNets Provably Better than Linear Predictors? 505-514 - Jun-Ting Hsieh, Bingbin Liu, De-An Huang, Li Fei-Fei, Juan Carlos Niebles:
Learning to Decompose and Disentangle Representations for Video Prediction. 515-524 - Ozan Sener, Vladlen Koltun:
Multi-Task Learning as Multi-Objective Optimization. 525-536 - Zhuwen Li, Qifeng Chen, Vladlen Koltun:
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search. 537-546 - Qibin Hou, Peng-Tao Jiang, Yunchao Wei, Ming-Ming Cheng:
Self-Erasing Network for Integral Object Attention. 547-557 - Sanghyun Woo, Dahun Kim, Donghyeon Cho, In So Kweon:
LinkNet: Relational Embedding for Scene Graph. 558-568 - Boris Hanin, David Rolnick:
How to Start Training: The Effect of Initialization and Architecture. 569-579 - Boris Hanin:
Which Neural Net Architectures Give Rise to Exploding and Vanishing Gradients? 580-589 - Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Pai-Shun Ting, Karthikeyan Shanmugam, Payel Das:
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives. 590-601 - Peiqi Wang, Xinfeng Xie, Lei Deng, Guoqi Li, Dongsheng Wang, Yuan Xie:
HitNet: Hybrid Ternary Recurrent Neural Network. 602-612 - Christian Kroer, Tuomas Sandholm:
A Unified Framework for Extensive-Form Game Abstraction with Bounds. 613-624 - Zijun Zhang, Yining Zhang, Zongpeng Li:
Removing the Feature Correlation Effect of Multiplicative Noise. 625-634 - Abhimanyu Dubey, Otkrist Gupta, Ramesh Raskar, Nikhil Naik:
Maximum-Entropy Fine Grained Classification. 635-645 - Yi Hao, Alon Orlitsky, Venkatadheeraj Pichapati:
On Learning Markov Chains. 646-655 - Bo Dai, Sanja Fidler, Dahua Lin:
A Neural Compositional Paradigm for Image Captioning. 656-666 - Kirill Struminsky, Simon Lacoste-Julien, Anton Osokin:
Quantifying Learning Guarantees for Convex but Inconsistent Surrogates. 667-675 - Xiaoxiao Guo, Hui Wu, Yu Cheng, Steven Rennie, Gerald Tesauro, Rogério Schmidt Feris:
Dialog-based Interactive Image Retrieval. 676-686 - Cong Fang, Chris Junchi Li, Zhouchen Lin, Tong Zhang:
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator. 687-697 - Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet:
Are GANs Created Equal? A Large-Scale Study. 698-707 - Emilien Dupont:
Learning Disentangled Joint Continuous and Discrete Representations. 708-718 - Boris N. Oreshkin, Pau Rodríguez López, Alexandre Lacoste:
TADAM: Task dependent adaptive metric for improved few-shot learning. 719-729 - Moran Feldman, Amin Karbasi, Ehsan Kazemi:
Do Less, Get More: Streaming Submodular Maximization with Subsampling. 730-740 - Rui Li, Kishan KC, Feng Cui, Justin Domke, Anne R. Haake:
Sparse Covariance Modeling in High Dimensions with Gaussian Processes. 741-750 - Bao Wang, Xiyang Luo, Zhen Li, Wei Zhu, Zuoqiang Shi, Stanley J. Osher:
Deep Neural Nets with Interpolating Function as Output Activation. 751-761 - Shuyang Sun, Jiangmiao Pang, Jianping Shi, Shuai Yi, Wanli Ouyang:
FishNet: A Versatile Backbone for Image, Region, and Pixel Level Prediction. 762-772 - Ashish Kumar, Saurabh Gupta, David F. Fouhey, Sergey Levine, Jitendra Malik:
Visual Memory for Robust Path Following. 773-782 - Xiaojie Wang, Rui Zhang, Yu Sun, Jianzhong Qi:
KDGAN: Knowledge Distillation with Generative Adversarial Networks. 783-794 - Guillaume Bellec, Darjan Salaj, Anand Subramoney, Robert Legenstein, Wolfgang Maass:
Long short-term memory and Learning-to-learn in networks of spiking neurons. 795-805 - Shupeng Su, Chao Zhang, Kai Han, Yonghong Tian:
Greedy Hash: Towards Fast Optimization for Accurate Hash Coding in CNN. 806-815 - Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy, James Hays, Bernhard Schölkopf, Arthur Gretton:
Informative Features for Model Comparison. 816-827 - Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, Baoquan Chen:
PointCNN: Convolution On X-Transformed Points. 828-838 - Hu Liu, Sheng Jin, Changshui Zhang:
Connectionist Temporal Classification with Maximum Entropy Regularization. 839-849 - Gamaleldin F. Elsayed, Dilip Krishnan, Hossein Mobahi, Kevin Regan, Samy Bengio:
Large Margin Deep Networks for Classification. 850-860 - Tianshu Yu, Junchi Yan, Yilin Wang, Wei Liu, Baoxin Li:
Generalizing Graph Matching beyond Quadratic Assignment Model. 861-871 - Christian Kroer, Gabriele Farina, Tuomas Sandholm:
Solving Large Sequential Games with the Excessive Gap Technique. 872-882 - Zhuangwei Zhuang, Mingkui Tan, Bohan Zhuang, Jing Liu, Yong Guo, Qingyao Wu, Junzhou Huang, Jin-Hui Zhu:
Discrimination-aware Channel Pruning for Deep Neural Networks. 883-894 - Zi Yin, Yuanyuan Shen:
On the Dimensionality of Word Embedding. 895-906 - Ju Xu, Zhanxing Zhu:
Reinforced Continual Learning. 907-916 - Jay Heo, Haebeom Lee, Saehoon Kim, Juho Lee, Kwang Joon Kim, Eunho Yang, Sung Ju Hwang:
Uncertainty-Aware Attention for Reliable Interpretation and Prediction. 917-926 - Haebeom Lee, Juho Lee, Saehoon Kim, Eunho Yang, Sung Ju Hwang:
DropMax: Adaptive Variational Softmax. 927-937 - Veronika Rocková, Nicholas Polson:
Posterior Concentration for Sparse Deep Learning. 938-949 - Guilhem Chéron, Jean-Baptiste Alayrac, Ivan Laptev, Cordelia Schmid:
A flexible model for training action localization with varying levels of supervision. 950-961 - Yan Zheng, Zhaopeng Meng, Jianye Hao, Zongzhang Zhang, Tianpei Yang, Changjie Fan:
A Deep Bayesian Policy Reuse Approach Against Non-Stationary Agents. 962-972 - Di Wang, Marco Gaboardi, Jinhui Xu:
Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited. 973-982 - Hang Gao, Zheng Shou, Alireza Zareian, Hanwang Zhang, Shih-Fu Chang:
Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks. 983-993 - Michel Deudon:
Learning semantic similarity in a continuous space. 994-1005 - Yogesh Balaji, Swami Sankaranarayanan, Rama Chellappa:
MetaReg: Towards Domain Generalization using Meta-Regularization. 1006-1016 - Lifang He, Kun Chen, Wanwan Xu, Jiayu Zhou, Fei Wang:
Boosted Sparse and Low-Rank Tensor Regression. 1017-1026 - An Zhao, Mingyu Ding, Jiechao Guan, Zhiwu Lu, Tao Xiang, Ji-Rong Wen:
Domain-Invariant Projection Learning for Zero-Shot Recognition. 1027-1038 - Kexin Yi, Jiajun Wu, Chuang Gan, Antonio Torralba, Pushmeet Kohli, Josh Tenenbaum:
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding. 1039-1050 - Zhenhua Liu, Jizheng Xu, Xiulian Peng, Ruiqin Xiong:
Frequency-Domain Dynamic Pruning for Convolutional Neural Networks. 1051-1061 - Pan Li, Niao He, Olgica Milenkovic:
Quadratic Decomposable Submodular Function Minimization. 1062-1072 - Tengyang Xie, Bo Liu, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu
, Daesub Yoon:
A Block Coordinate Ascent Algorithm for Mean-Variance Optimization. 1073-1083 - Lijun Zhang, Zhi-Hua Zhou:
\ell_1-regression with Heavy-tailed Distributions. 1084-1094 - Tobias Plötz, Stefan Roth:
Neural Nearest Neighbors Networks. 1095-1106 - Shali Jiang, Gustavo Malkomes, Matthew Abbott, Benjamin Moseley, Roman Garnett:
Efficient nonmyopic batch active search. 1107-1117 - Omer Ben-Porat, Moshe Tennenholtz:
A Game-Theoretic Approach to Recommendation Systems with Strategic Content Providers. 1118-1128 - Christopher Tosh, Sanjoy Dasgupta:
Interactive Structure Learning with Structural Query-by-Committee. 1129-1139 - Yanjun Li, Yoram Bresler:
Global Geometry of Multichannel Sparse Blind Deconvolution on the Sphere. 1140-1151 - Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Nikolai Yakovenko, Andrew Tao, Jan Kautz, Bryan Catanzaro:
Video-to-Video Synthesis. 1152-1164 - Zeyuan Allen-Zhu:
How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD. 1165-1175 - Hexiang Hu, Liyu Chen, Boqing Gong, Fei Sha:
Synthesize Policies for Transfer and Adaptation across Tasks and Environments. 1176-1185 - Alhussein Fawzi, Hamza Fawzi, Omar Fawzi:
Adversarial vulnerability for any classifier. 1186-1195 - Shauharda Khadka, Kagan Tumer:
Evolution-Guided Policy Gradient in Reinforcement Learning. 1196-1208 - Sven Bambach, David J. Crandall, Linda B. Smith, Chen Yu:
Toddler-Inspired Visual Object Learning. 1209-1218 - Miguel Á. Carreira-Perpiñán, Pooya Tavallali:
Alternating optimization of decision trees, with application to learning sparse oblique trees. 1219-1229 - Yixiao Ge, Zhuowan Li, Haiyu Zhao, Guojun Yin, Shuai Yi, Xiaogang Wang, Hongsheng Li:
FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification. 1230-1241 - Pan Zhou, Xiaotong Yuan, Jiashi Feng:
New Insight into Hybrid Stochastic Gradient Descent: Beyond With-Replacement Sampling and Convexity. 1242-1251 - Zeyuan Allen-Zhu, David Simchi-Levi, Xinshang Wang:
The Lingering of Gradients: How to Reuse Gradients Over Time. 1252-1261 - Junnan Li, Yongkang Wong, Qi Zhao, Mohan S. Kankanhalli:
Unsupervised Learning of View-invariant Action Representations. 1262-1272 - Hoda Heidari, Claudio Ferrari, Krishna P. Gummadi, Andreas Krause:
Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making. 1273-1283 - Qilong Wang, Zilin Gao, Jiangtao Xie, Wangmeng Zuo, Peihua Li:
Global Gated Mixture of Second-order Pooling for Improving Deep Convolutional Neural Networks. 1284-1293 - Abel Gonzalez-Garcia, Joost van de Weijer, Yoshua Bengio:
Image-to-image translation for cross-domain disentanglement. 1294-1305