Papers
Near-Optimal Differentially Private Reinforcement Learning
Dan Qiao, Yu-Xiang Wang
Neural Discovery of Permutation Subgroups
Pavan Karjol, Rohan Kashyap, Prathosh AP
Neural Laplace Control for Continuous-time Delayed Systems
Samuel Holt, Alihan Hüyük, Zhaozhi Qian et al.
Neural Simulated Annealing
Alvaro H.C. Correia, Daniel E. Worrall, Roberto Bondesan
NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning
Muralikrishnna G Sethuraman, Romain Lopez, Rahul Mohan et al.
Noise-Aware Statistical Inference with Differentially Private Synthetic Data
Ossi Räisä, Joonas Jälkö, Samuel Kaski et al.
Noisy Low-rank Matrix Optimization: Geometry of Local Minima and Convergence Rate
Ziye Ma, Somayeh Sojoudi
Nonmyopic Multiclass Active Search with Diminishing Returns for Diverse Discovery
Quan Nguyen, Roman Garnett
Nonparametric Gaussian Process Covariances via Multidimensional Convolutions
Thomas M. Mcdonald, Magnus Ross, Michael T. Smith et al.
Nonparametric Indirect Active Learning
Shashank Singh
Nonstationary Bandit Learning via Predictive Sampling
Yueyang Liu, Benjamin Van Roy, Kuang Xu
Nonstochastic Contextual Combinatorial Bandits
Lukas Zierahn, Dirk van der Hoeven, Nicolò Cesa-Bianchi et al.
No-Regret Learning in Two-Echelon Supply Chain with Unknown Demand Distribution
Mengxiao Zhang, Shi Chen, Haipeng Luo et al.
No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities
Sebastian Shenghong Tay, Quoc Phong Nguyen, Chuan Sheng Foo et al.
Nothing but Regrets — Privacy-Preserving Federated Causal Discovery
Osman Mian, David Kaltenpoth, Michael Kamp et al.
No time to waste: practical statistical contact tracing with few low-bit messages
Rob Romijnders, Yuki M. Asano, Christos Louizos et al.
NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge
Xiangyu Sun, Oliver Schulte, Guiliang Liu et al.
Nyström Method for Accurate and Scalable Implicit Differentiation
Ryuichiro Hataya, Makoto Yamada
Oblivious near-optimal sampling for multidimensional signals with Fourier constraints
Xingyu Xu, Yuantao Gu
On-Demand Communication for Asynchronous Multi-Agent Bandits
Yu-Zhen Janice Chen, Lin Yang, Xuchuang Wang et al.
On double-descent in uncertainty quantification in overparametrized models
Lucas Clarte, Bruno Loureiro, Florent Krzakala et al.
One Arrow, Two Kills: A Unified Framework for Achieving Optimal Regret Guarantees in Sleeping Bandits
Pierre Gaillard, Aadirupa Saha, Soham Dan
One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning
Pedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo et al.
On Generalization of Decentralized Learning with Separable Data
Hossein Taheri, Christos Thrampoulidis
Online Algorithms with Costly Predictions
Marina Drygala, Sai Ganesh Nagarajan, Ola Svensson