NIPS

Publications

2017

Anna Volokitin, Gemma Roig, Tomaso A. Poggio
Do Deep Neural Networks Suffer from Crowding? NIPS (2017)
ChengYue Gong, Win-Bin Huang
Deep Dynamic Poisson Factorization Model. NIPS (2017)
Adam R. Kosiorek, Alex Bewley, Ingmar Posner
Hierarchical Attentive Recurrent Tracking. NIPS (2017)
Songbai Yan, Chicheng Zhang
Revisiting Perceptron: Efficient and Label-Optimal Learning of Halfspaces. NIPS (2017)
Wei-Sheng Lai, Jia-Bin Huang, Ming-Hsuan Yang
Semi-Supervised Learning for Optical Flow with Generative Adversarial Networks. NIPS (2017)
Daniele Calandriello, Alessandro Lazaric, Michal Valko
Efficient Second-Order Online Kernel Learning with Adaptive Embedding. NIPS (2017)
Quentin Berthet, Vianney Perchet
Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe. NIPS (2017)
Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau
Policy Gradient With Value Function Approximation For Collective Multiagent Planning. NIPS (2017)
Simon S. Du, Yining Wang, Aarti Singh
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems. NIPS (2017)
Zelda E. Mariet, Suvrit Sra
Elementary Symmetric Polynomials for Optimal Experimental Design. NIPS (2017)
Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, Pieter Abbeel, Igor Mordatch
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. NIPS (2017)
Di Wang, Minwei Ye, Jinhui Xu
Differentially Private Empirical Risk Minimization Revisited: Faster and More General. NIPS (2017)
Jianbo Chen, Mitchell Stern, Martin J. Wainwright, Michael I. Jordan
Kernel Feature Selection via Conditional Covariance Minimization. NIPS (2017)
Yuanzhi Li, Yang Yuan
Convergence Analysis of Two-layer Neural Networks with ReLU Activation. NIPS (2017)
Asier Mujika, Florian Meier, Angelika Steger
Fast-Slow Recurrent Neural Networks. NIPS (2017)
Tim Rocktäschel, Sebastian Riedel
End-to-end Differentiable Proving. NIPS (2017)
Günter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter
Self-Normalizing Neural Networks. NIPS (2017)
Zelun Luo, Yuliang Zou, Judy Hoffman, Li Fei-Fei
Label Efficient Learning of Transferable Representations acrosss Domains and Tasks. NIPS (2017)
S. Hamed Hassani, Mahdi Soltanolkotabi, Amin Karbasi
Gradient Methods for Submodular Maximization. NIPS (2017)
Jeffrey Pennington, Samuel S. Schoenholz, Surya Ganguli
Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice. NIPS (2017)
Chao-Bing Song, Shaobo Cui, Yong Jiang, Shu-Tao Xia
Accelerated Stochastic Greedy Coordinate Descent by Soft Thresholding Projection onto Simplex. NIPS (2017)
Yuanbin Wu, Man Lan, Shiliang Sun, Qi Zhang, Xuanjing Huang
A Learning Error Analysis for Structured Prediction with Approximate Inference. NIPS (2017)
Kwang-Sung Jun, Aniruddha Bhargava, Robert D. Nowak, Rebecca Willett
Scalable Generalized Linear Bandits: Online Computation and Hashing. NIPS (2017)
Le Song, Santosh S. Vempala, John Wilmes, Bo Xie
On the Complexity of Learning Neural Networks. NIPS (2017)
Paul F. Christiano, Jan Leike, Tom B. Brown, Miljan Martic, Shane Legg, Dario Amodei
Deep Reinforcement Learning from Human Preferences. NIPS (2017)
Tao Sun, Robert Hannah, Wotao Yin
Asynchronous Coordinate Descent under More Realistic Assumptions. NIPS (2017)
Wittawat Jitkrittum, Wenkai Xu, Zoltán Szabó, Kenji Fukumizu, Arthur Gretton
A Linear-Time Kernel Goodness-of-Fit Test. NIPS (2017)
Muhammad Yousefnezhad, Daoqiang Zhang
Deep Hyperalignment. NIPS (2017)
Ping Li, Martin Slawski
Simple strategies for recovering inner products from coarsely quantized random projections. NIPS (2017)
Nir Levine, Tom Zahavy, Daniel J. Mankowitz, Aviv Tamar, Shie Mannor
Shallow Updates for Deep Reinforcement Learning. NIPS (2017)
Shiyu Chang, Yang Zhang, Wei Han, Mo Yu, Xiaoxiao Guo, Wei Tan, Xiaodong Cui, Michael J. Witbrock, Mark A. Hasegawa-Johnson, Thomas S. Huang
Dilated Recurrent Neural Networks. NIPS (2017)
Eleni Triantafillou, Richard S. Zemel, Raquel Urtasun
Few-Shot Learning Through an Information Retrieval Lens. NIPS (2017)
Siddharth Narayanaswamy, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah D. Goodman, Pushmeet Kohli, Frank D. Wood, Philip H. S. Torr
Learning Disentangled Representations with Semi-Supervised Deep Generative Models. NIPS (2017)
Han Zhao, Geoffrey J. Gordon
Linear Time Computation of Moments in Sum-Product Networks. NIPS (2017)
Alireza Makhzani, Brendan J. Frey
PixelGAN Autoencoders. NIPS (2017)
Artur Speiser, Jinyao Yan, Evan W. Archer, Lars Buesing, Srinivas C. Turaga, Jakob H. Macke
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders. NIPS (2017)
Jonathan Peck, Joris Roels, Bart Goossens, Yvan Saeys
Lower bounds on the robustness to adversarial perturbations. NIPS (2017)
Yunus Saatci, Andrew Gordon Wilson
Bayesian GAN. NIPS (2017)
Yi-An Lai, Chin-Chi Hsu, Wen-Hao Chen, Mi-Yen Yeh, Shou-De Lin
PRUNE: Preserving Proximity and Global Ranking for Network Embedding. NIPS (2017)
Christopher A. Metzler, Ali Mousavi, Richard G. Baraniuk
Learned D-AMP: Principled Neural Network based Compressive Image Recovery. NIPS (2017)
Tomer Koren, Roi Livni
Affine-Invariant Online Optimization and the Low-rank Experts Problem. NIPS (2017)
Christian Borgs, Jennifer T. Chayes, Christina E. Lee, Devavrat Shah
Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation. NIPS (2017)
Yi Ouyang, Mukul Gagrani, Ashutosh Nayyar, Rahul Jain
Learning Unknown Markov Decision Processes: A Thompson Sampling Approach. NIPS (2017)
Michael Eickenberg, Georgios Exarchakis, Matthew J. Hirn, Stéphane Mallat
Solid Harmonic Wavelet Scattering: Predicting Quantum Molecular Energy from Invariant Descriptors of 3D Electronic Densities. NIPS (2017)
Erinc Merdivan, Mohammad Reza Loghmani, Matthieu Geist
Reconstruct & Crush Network. NIPS (2017)
Xiangru Huang, Zhenxiao Liang, Chandrajit Bajaj, Qixing Huang
Translation Synchronization via Truncated Least Squares. NIPS (2017)
Edouard Grave, Moustapha Cissé, Armand Joulin
Unbounded cache model for online language modeling with open vocabulary. NIPS (2017)
Mingsheng Long, Zhangjie Cao, Jianmin Wang, Philip S. Yu
Learning Multiple Tasks with Multilinear Relationship Networks. NIPS (2017)
Zhijie Deng, Hao Zhang, Xiaodan Liang, Luona Yang, Shizhen Xu, Jun Zhu, Eric P. Xing
Structured Generative Adversarial Networks. NIPS (2017)
Ethan R. Elenberg, Alexandros G. Dimakis, Moran Feldman, Amin Karbasi
Streaming Weak Submodularity: Interpreting Neural Networks on the Fly. NIPS (2017)