Papers
Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning"
Saeed Amizadeh, Hamid Palangi, Alex Polozov et al.
New Oracle-Efficient Algorithms for Private Synthetic Data Release
Giuseppe Vietri, Grace Tian, Mark Bun et al.
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Tony Duan, Avati Anand, Daisy Yi Ding et al.
Non-autoregressive Machine Translation with Disentangled Context Transformer
Jungo Kasai, James Cross, Marjan Ghazvininejad et al.
Non-Autoregressive Neural Text-to-Speech
Kainan Peng, Wei Ping, Zhao Song et al.
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
Wei Deng, Qi Feng, Liyao Gao et al.
Nonparametric Score Estimators
Yuhao Zhou, Jiaxin Shi, Jun Zhu
Non-separable Non-stationary random fields
Kangrui Wang, Oliver Hamelijnck, Theodoros Damoulas et al.
Non-Stationary Delayed Bandits with Intermediate Observations
Claire Vernade, Andras Gyorgy, Timothy Mann
No-Regret and Incentive-Compatible Online Learning
Rupert Freeman, David Pennock, Chara Podimata et al.
No-Regret Exploration in Goal-Oriented Reinforcement Learning
Jean Tarbouriech, Evrard Garcelon, Michal Valko et al.
Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis
Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama
Normalized Loss Functions for Deep Learning with Noisy Labels
Xingjun Ma, Hanxun Huang, Yisen Wang et al.
Normalizing Flows on Tori and Spheres
Danilo Jimenez Rezende, George Papamakarios, Sebastien Racaniere et al.
Obtaining Adjustable Regularization for Free via Iterate Averaging
Jingfeng Wu, Vladimir Braverman, Lin Yang
Off-Policy Actor-Critic with Shared Experience Replay
Simon Schmitt, Matteo Hessel, Karen Simonyan
On Approximate Thompson Sampling with Langevin Algorithms
Eric Mazumdar, Aldo Pacchiano, Yian Ma et al.
On a projective ensemble approach to two sample test for equality of distributions
Zhimei Li, Yaowu Zhang
On Breaking Deep Generative Model-based Defenses and Beyond
Yanzhi Chen, Renjie Xie, Zhanxing Zhu
On Conditional Versus Marginal Bias in Multi-Armed Bandits
Jaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo
On Contrastive Learning for Likelihood-free Inference
Conor Durkan, Iain Murray, George Papamakarios
On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent
Scott Pesme, Aymeric Dieuleveut, Nicolas Flammarion
On Coresets for Regularized Regression
Rachit Chhaya, Anirban Dasgupta, Supratim Shit
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data
Di Wang, Hanshen Xiao, Srinivas Devadas et al.
On Efficient Constructions of Checkpoints
Yu Chen, Zhenming Liu, Bin Ren et al.