Papers
Nested Subspace Arrangement for Representation of Relational Data
Nozomi Hata, Shizuo Kaji, Akihiro Yoshida et al.
NetGAN without GAN: From Random Walks to Low-Rank Approximations
Luca Rendsburg, Holger Heidrich, Ulrike Von Luxburg
Neural Architecture Search in A Proxy Validation Loss Landscape
Yanxi Li, Minjing Dong, Yunhe Wang et al.
Neural Clustering Processes
Ari Pakman, Yueqi Wang, Catalin Mitelut et al.
Neural Contextual Bandits with UCB-based Exploration
Dongruo Zhou, Lihong Li, Quanquan Gu
Neural Datalog Through Time: Informed Temporal Modeling via Logical Specification
Hongyuan Mei, Guanghui Qin, Minjie Xu et al.
Neural Kernels Without Tangents
Vaishaal Shankar, Alex Fang, Wenshuo Guo et al.
Neural Network Control Policy Verification With Persistent Adversarial Perturbation
Yuh-Shyang Wang, Lily Weng, Luca Daniel
Neural Topic Modeling with Continual Lifelong Learning
Pankaj Gupta, Yatin Chaudhary, Thomas Runkler et al.
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