Papers
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.
Obtaining Fairness using Optimal Transport Theory
Paula Gordaliza, Eustasio Del Barrio, Gamboa Fabrice et al.
Off-Policy Deep Reinforcement Learning without Exploration
Scott Fujimoto, David Meger, Doina Precup
On Certifying Non-Uniform Bounds against Adversarial Attacks
Chen Liu, Ryota Tomioka, Volkan Cevher
On Connected Sublevel Sets in Deep Learning
Quynh Nguyen
On discriminative learning of prediction uncertainty
Vojtech Franc, Daniel Prusa
On Dropout and Nuclear Norm Regularization
Poorya Mianjy, Raman Arora
On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms
Tianyi Lin, Nhat Ho, Michael Jordan
On Learning Invariant Representations for Domain Adaptation
Han Zhao, Remi Tachet Des Combes, Kun Zhang et al.
Online Adaptive Principal Component Analysis and Its extensions
Jianjun Yuan, Andrew Lamperski
Online Algorithms for Rent-Or-Buy with Expert Advice
Sreenivas Gollapudi, Debmalya Panigrahi