| 2021 | Gradient Descent in RKHS with Importance Labeling. | Tomoya Murata, Taiji Suzuki |
| 2021 | Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models. | Sasi Kumar Murakonda, Reza Shokri, George Theodorakopoulos |
| 2021 | Private optimization without constraint violations. | Andrs Muoz Medina, Umar Syed, Sergei Vassilvitskii, Ellen Vitercik |
| 2021 | Stochastic Gradient Descent Meets Distribution Regression. | Nicole Mcke |
| 2021 | On the Convergence of Gradient Descent in GANs: MMD GAN As a Gradient Flow. | Youssef Mroueh, Truyen Nguyen |
| 2021 | Hierarchical Clustering in General Metric Spaces using Approximate Nearest Neighbors. | Benjamin Moseley, Sergei Vassilvitskii, Yuyan Wang |
| 2021 | Automatic Differentiation Variational Inference with Mixtures. | Warren R. Morningstar, Sharad M. Vikram, Cusuh Ham, Andrew G. Gallagher, Joshua V. Dillon |
| 2021 | Density of States Estimation for Out of Distribution Detection. | Warren R. Morningstar, Cusuh Ham, Andrew G. Gallagher, Balaji Lakshminarayanan, Alexander A. Alemi, Joshua V. Dillon |
| 2021 | Independent Innovation Analysis for Nonlinear Vector Autoregressive Process. | Hiroshi Morioka, Hermanni Hlv, Aapo Hyvrinen |
| 2021 | Approximate Message Passing with Spectral Initialization for Generalized Linear Models. | Marco Mondelli, Ramji Venkataramanan |
| 2021 | DAG-Structured Clustering by Nearest Neighbors. | Nicholas Monath, Manzil Zaheer, Kumar Avinava Dubey, Amr Ahmed, Andrew McCallum |
| 2021 | Iterative regularization for convex regularizers. | Cesare Molinari, Mathurin Massias, Lorenzo Rosasco, Silvia Villa |
| 2021 | Hidden Cost of Randomized Smoothing. | Jeet Mohapatra, Ching-Yun Ko, Lily Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel |
| 2021 | Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions in Medical Domain. | Takahiro Mimori, Keiko Sasada, Hirotaka Matsui, Issei Sato |
| 2021 | Tensor Networks for Probabilistic Sequence Modeling. | Jacob Miller, Guillaume Rabusseau, John Terilla |
| 2021 | Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors. | Nikhil Mehta, Kevin J. Liang, Vinay Kumar Verma, Lawrence Carin |
| 2021 | Differentiating the Value Function by using Convex Duality. | Sheheryar Mehmood, Peter Ochs |
| 2021 | Location Trace Privacy Under Conditional Priors. | Casey Meehan, Kamalika Chaudhuri |
| 2021 | Semi-Supervised Aggregation of Dependent Weak Supervision Sources With Performance Guarantees. | Alessio Mazzetto, Dylan Sam, Andrew Park, Eli Upfal, Stephen H. Bach |
| 2021 | Collaborative Classification from Noisy Labels. | Lucas Maystre, Nagarjuna Kumarappan, Judith Btepage, Mounia Lalmas |
| 2021 | Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side-Information. | Prathamesh Mayekar, Ananda Theertha Suresh, Himanshu Tyagi |
| 2021 | Tracking Regret Bounds for Online Submodular Optimization. | Tatsuya Matsuoka, Shinji Ito, Naoto Ohsaka |
| 2021 | Causal Inference under Networked Interference and Intervention Policy Enhancement. | Yunpu Ma, Volker Tresp |
| 2021 | Reaping the Benefits of Bundling under High Production Costs. | Will Ma, David Simchi-Levi |
| 2021 | Misspecification in Prediction Problems and Robustness via Improper Learning. | Annie Marsden, John C. Duchi, Gregory Valiant |