| 2022 | Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets. | Felix L. Opolka, Yin-Cong Zhi, Pietro Li, Xiaowen Dong |
| 2022 | Bayesian Link Prediction with Deep Graph Convolutional Gaussian Processes. | Felix L. Opolka, Pietro Li |
| 2022 | One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and Limitation. | Hajime Ono, Kazuhiro Minami, Hideitsu Hino |
| 2022 | Robustness and Reliability When Training With Noisy Labels. | Amanda Olmin, Fredrik Lindsten |
| 2022 | On the Consistency of Max-Margin Losses. | Alex Nowak, Alessandro Rudi, Francis R. Bach |
| 2022 | Differentially Private Federated Learning on Heterogeneous Data. | Maxence Noble, Aurlien Bellet, Aymeric Dieuleveut |
| 2022 | Multi-class classification in nonparametric active learning. | Boris Ndjia Njike, Xavier Siebert |
| 2022 | Can Functional Transfer Methods Capture Simple Inductive Biases? | Arne Nix, Suhas Shrinivasan, Edgar Y. Walker, Fabian H. Sinz |
| 2022 | Convex Analysis of the Mean Field Langevin Dynamics. | Atsushi Nitanda, Denny Wu, Taiji Suzuki |
| 2022 | Non-separable Spatio-temporal Graph Kernels via SPDEs. | Alexander Nikitin, S. T. John, Arno Solin, Samuel Kaski |
| 2022 | Outlier-Robust Optimal Transport: Duality, Structure, and Statistical Analysis. | Sloan Nietert, Ziv Goldfeld, Rachel Cummings |
| 2022 | Many processors, little time: MCMC for partitions via optimal transport couplings. | Tin D. Nguyen, Brian L. Trippe, Tamara Broderick |
| 2022 | Federated Learning with Buffered Asynchronous Aggregation. | John Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Mike Rabbat, Mani Malek, Dzmitry Huba |
| 2022 | The Importance of Future Information in Credit Card Fraud Detection. | Van Bach Nguyen, Kanishka Ghosh Dastidar, Michael Granitzer, Wissam Siblini |
| 2022 | Particle-based Adversarial Local Distribution Regularization. | Thanh Nguyen-Duc, Trung Le, He Zhao, Jianfei Cai, Dinh Q. Phung |
| 2022 | On the Convergence of Continuous Constrained Optimization for Structure Learning. | Ignavier Ng, Sbastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien, Kun Zhang |
| 2022 | Towards Federated Bayesian Network Structure Learning with Continuous Optimization. | Ignavier Ng, Kun Zhang |
| 2022 | Orbital MCMC. | Kirill Neklyudov, Max Welling |
| 2022 | Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes. | Elvis Nava, Mojmir Mutny, Andreas Krause |
| 2022 | Learning in Stochastic Monotone Games with Decision-Dependent Data. | Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff |
| 2022 | Compressed Rule Ensemble Learning. | Malte Nalenz, Thomas Augustin |
| 2022 | Nonparametric Relational Models with Superrectangulation. | Masahiro Nakano, Ryo Nishikimi, Yasuhiro Fujiwara, Akisato Kimura, Takeshi Yamada, Naonori Ueda |
| 2022 | Amortized Rejection Sampling in Universal Probabilistic Programming. | Saeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atilim Gunes Baydin, Bradley J. Gram-Hansen, Christian A. Schrder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood |
| 2022 | Reward-Free Policy Space Compression for Reinforcement Learning. | Mirco Mutti, Stefano Del Col, Marcello Restelli |
| 2022 | Sensing Cox Processes via Posterior Sampling and Positive Bases. | Mojmir Mutny, Andreas Krause |