Papers
Neural Autoregressive Flows
Chin-Wei Huang, David Krueger, Alexandre Lacoste et al.
Neural Dynamic Programming for Musical Self Similarity
Christian Walder, Dongwoo Kim
Neural Inverse Rendering for General Reflectance Photometric Stereo
Tatsunori Taniai, Takanori Maehara
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions
Quynh Nguyen, Mahesh Chandra Mukkamala, Matthias Hein
Neural Program Synthesis from Diverse Demonstration Videos
Shao-Hua Sun, Hyeonwoo Noh, Sriram Somasundaram et al.
Neural Relational Inference for Interacting Systems
Thomas Kipf, Ethan Fetaya, Kuan-Chieh Wang et al.
Noise2Noise: Learning Image Restoration without Clean Data
Jaakko Lehtinen, Jacob Munkberg, Jon Hasselgren et al.
Noisin: Unbiased Regularization for Recurrent Neural Networks
Adji Bousso Dieng, Rajesh Ranganath, Jaan Altosaar et al.
Noisy Natural Gradient as Variational Inference
Guodong Zhang, Shengyang Sun, David Duvenaud et al.
Non-convex Conditional Gradient Sliding
Chao Qu, Yan Li, Huan Xu
Nonconvex Optimization for Regression with Fairness Constraints
Junpei Komiyama, Akiko Takeda, Junya Honda et al.
Non-linear motor control by local learning in spiking neural networks
Aditya Gilra, Wulfram Gerstner
Nonoverlap-Promoting Variable Selection
Pengtao Xie, Hongbao Zhang, Yichen Zhu et al.
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information
Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan et al.
Nonparametric variable importance using an augmented neural network with multi-task learning
Jean Feng, Brian Williamson, Noah Simon et al.
Not All Samples Are Created Equal: Deep Learning with Importance Sampling
Angelos Katharopoulos, Francois Fleuret
Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical Care
Patrick Schwab, Emanuela Keller, Carl Muroi et al.
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye, Nicholas Carlini, David Wagner
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis
Samuel K. Ainsworth, Nicholas J. Foti, Adrian K. C. Lee et al.
On Acceleration with Noise-Corrupted Gradients
Michael Cohen, Jelena Diakonikolas, Lorenzo Orecchia
One-Shot Segmentation in Clutter
Claudio Michaelis, Matthias Bethge, Alexander Ecker
On Learning Sparsely Used Dictionaries from Incomplete Samples
Thanh Nguyen, Akshay Soni, Chinmay Hegde
Online Convolutional Sparse Coding with Sample-Dependent Dictionary
Yaqing Wang, Quanming Yao, James Tin-Yau Kwok et al.
Online Learning with Abstention
Corinna Cortes, Giulia DeSalvo, Claudio Gentile et al.
Online Linear Quadratic Control
Alon Cohen, Avinatan Hasidim, Tomer Koren et al.