Papers
Mitigating Bias in Adaptive Data Gathering via Differential Privacy
Seth Neel, Aaron Roth
Mixed batches and symmetric discriminators for GAN training
Thomas LUCAS, Corentin Tallec, Yann Ollivier et al.
Mix & Match Agent Curricula for Reinforcement Learning
Wojciech Czarnecki, Siddhant Jayakumar, Max Jaderberg et al.
Modeling Others using Oneself in Multi-Agent Reinforcement Learning
Roberta Raileanu, Emily Denton, Arthur Szlam et al.
Modeling Sparse Deviations for Compressed Sensing using Generative Models
Manik Dhar, Aditya Grover, Stefano Ermon
Model-Level Dual Learning
Yingce Xia, Xu Tan, Fei Tian et al.
More Robust Doubly Robust Off-policy Evaluation
Mehrdad Farajtabar, Yinlam Chow, Mohammad Ghavamzadeh
MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning
Bo Zhao, Xinwei Sun, Yanwei Fu et al.
Multicalibration: Calibration for the (Computationally-Identifiable) Masses
Ursula Hebert-Johnson, Michael Kim, Omer Reingold et al.
Multi-Fidelity Black-Box Optimization with Hierarchical Partitions
Rajat Sen, Kirthevasan Kandasamy, Sanjay Shakkottai
Mutual Information Neural Estimation
Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeshwar et al.
Nearly Optimal Robust Subspace Tracking
Praneeth Narayanamurthy, Namrata Vaswani
NetGAN: Generating Graphs via Random Walks
Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner et al.
Network Global Testing by Counting Graphlets
Jiashun Jin, Zheng Ke, Shengming Luo
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