Papers
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments
Kirthevasan Kandasamy, Willie Neiswanger, Reed Zhang et al.
NAS-Bench-101: Towards Reproducible Neural Architecture Search
Chris Ying, Aaron Klein, Eric Christiansen et al.
NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks
Yandong Li, Lijun Li, Liqiang Wang et al.
Natural Analysts in Adaptive Data Analysis
Tijana Zrnic, Moritz Hardt
Near optimal finite time identification of arbitrary linear dynamical systems
Tuhin Sarkar, Alexander Rakhlin
Neural Collaborative Subspace Clustering
Tong Zhang, Pan Ji, Mehrtash Harandi et al.
Neural Inverse Knitting: From Images to Manufacturing Instructions
Alexandre Kaspar, Tae-Hyun Oh, Liane Makatura et al.
Neural Joint Source-Channel Coding
Kristy Choi, Kedar Tatwawadi, Aditya Grover et al.
Neural Logic Reinforcement Learning
Zhengyao Jiang, Shan Luo
Neurally-Guided Structure Inference
Sidi Lu, Jiayuan Mao, Joshua Tenenbaum et al.
Neural Network Attributions: A Causal Perspective
Aditya Chattopadhyay, Piyushi Manupriya, Anirban Sarkar et al.
Neural Separation of Observed and Unobserved Distributions
Tavi Halperin, Ariel Ephrat, Yedid Hoshen
Neuron birth-death dynamics accelerates gradient descent and converges asymptotically
Grant Rotskoff, Samy Jelassi, Joan Bruna et al.
New results on information theoretic clustering
Ferdinando Cicalese, Eduardo Laber, Lucas Murtinho
Noise2Self: Blind Denoising by Self-Supervision
Joshua Batson, Loic Royer
Noisy Dual Principal Component Pursuit
Tianyu Ding, Zhihui Zhu, Tianjiao Ding et al.
Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization
Than Huy Nguyen, Umut Simsekli, Gael Richard
Nonconvex Variance Reduced Optimization with Arbitrary Sampling
Samuel Horváth, Peter Richtarik
Nonlinear Distributional Gradient Temporal-Difference Learning
Chao Qu, Shie Mannor, Huan Xu
Nonlinear Stein Variational Gradient Descent for Learning Diversified Mixture Models
Dilin Wang, Qiang Liu
Non-monotone Submodular Maximization with Nearly Optimal Adaptivity and Query Complexity
Matthew Fahrbach, Vahab Mirrokni, Morteza Zadimoghaddam
Non-Monotonic Sequential Text Generation
Sean Welleck, Kianté Brantley, Hal Daumé Iii et al.
Nonparametric Bayesian Deep Networks with Local Competition
Konstantinos Panousis, Sotirios Chatzis, Sergios Theodoridis
Non-Parametric Priors For Generative Adversarial Networks
Rajhans Singh, Pavan Turaga, Suren Jayasuriya et al.