| 2021 | Transforming Gaussian Processes With Normalizing Flows. | Juan Maroas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas |
| 2021 | High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding. | Hannah Marienwald, Jean-Baptiste Fermanian, Gilles Blanchard |
| 2021 | An Analysis of LIME for Text Data. | Dina Mardaoui, Damien Garreau |
| 2021 | A Theory of Multiple-Source Adaptation with Limited Target Labeled Data. | Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh, Ke Wu |
| 2021 | Fast Adaptation with Linearized Neural Networks. | Wesley J. Maddox, Shuai Tang, Pablo Garcia Moreno, Andrew Gordon Wilson, Andreas C. Damianou |
| 2021 | Cluster Trellis: Data Structures & Algorithms for Exact Inference in Hierarchical Clustering. | Sebastian Macaluso, Craig S. Greenberg, Nicholas Monath, Ji Ah Lee, Patrick Flaherty, Kyle Cranmer, Andrew McGregor, Andrew McCallum |
| 2021 | On the Effect of Auxiliary Tasks on Representation Dynamics. | Clare Lyle, Mark Rowland, Georg Ostrovski, Will Dabney |
| 2021 | Low-Rank Generalized Linear Bandit Problems. | Yangyi Lu, Amirhossein Meisami, Ambuj Tewari |
| 2021 | Benchmarking Simulation-Based Inference. | Jan-Matthis Lueckmann, Jan Boelts, David S. Greenberg, Pedro J. Gonalves, Jakob H. Macke |
| 2021 | Hyperbolic graph embedding with enhanced semi-implicit variational inference. | Ali Lotfi-Rezaabad, Rahi Kalantari, Sriram Vishwanath, Mingyuan Zhou, Jonathan I. Tamir |
| 2021 | Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence. | Nicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien |
| 2021 | Unifying Clustered and Non-stationary Bandits. | Chuanhao Li, Qingyun Wu, Hongning Wang |
| 2021 | Tight Regret Bounds for Infinite-armed Linear Contextual Bandits. | Yingkai Li, Yining Wang, Xi Chen, Yuan Zhou |
| 2021 | Online Forgetting Process for Linear Regression Models. | Yuantong Li, Chi-Hua Wang, Guang Cheng |
| 2021 | Contrastive learning of strong-mixing continuous-time stochastic processes. | Bingbin Liu, Pradeep Ravikumar, Andrej Risteski |
| 2021 | Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization. | Tianyi Liu, Yan Li, Song Wei, Enlu Zhou, Tuo Zhao |
| 2021 | Kernel regression in high dimensions: Refined analysis beyond double descent. | Fanghui Liu, Zhenyu Liao, Johan A. K. Suykens |
| 2021 | Learning with Hyperspherical Uniformity. | Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schlkopf, Adrian Weller |
| 2021 | Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures. | Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan A. K. Suykens |
| 2021 | Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon. | Jeremiah Z. Liu |
| 2021 | Smooth Bandit Optimization: Generalization to Holder Space. | Yusha Liu, Yining Wang, Aarti Singh |
| 2021 | Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning. | Chong Liu, Yuqing Zhu, Kamalika Chaudhuri, Yu-Xiang Wang |
| 2021 | On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification. | Tianyi Lin, Zeyu Zheng, Elynn Y. Chen, Marco Cuturi, Michael I. Jordan |
| 2021 | Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks. | Huichen Li, Linyi Li, Xiaojun Xu, Xiaolu Zhang, Shuang Yang, Bo Li |
| 2021 | Model updating after interventions paradoxically introduces bias. | James Liley, Samuel R. Emerson, Bilal A. Mateen, Catalina A. Vallejos, Louis J. M. Aslett, Sebastian J. Vollmer |