| 2021 | Minimal enumeration of all possible total effects in a Markov equivalence class. | F. Richard Guo, Emilija Perkovic |
| 2021 | Consistent k-Median: Simpler, Better and Robust. | Xiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian |
| 2021 | Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings. | Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, David Wipf |
| 2021 | Latent variable modeling with random features. | Gregory W. Gundersen, Michael Minyi Zhang, Barbara E. Engelhardt |
| 2021 | Mirrorless Mirror Descent: A Natural Derivation of Mirror Descent. | Suriya Gunasekar, Blake E. Woodworth, Nathan Srebro |
| 2021 | A Study of Condition Numbers for First-Order Optimization. | Charles Guille-Escuret, Manuela Girotti, Baptiste Goujaud, Ioannis Mitliagkas |
| 2021 | When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence. | Ziwei Guan, Tengyu Xu, Yingbin Liang |
| 2021 | High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation. | Kristjan H. Greenewald, Karthikeyan Shanmugam, Dmitriy A. Katz |
| 2021 | Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs. | Alden Green, Sivaraman Balakrishnan, Ryan J. Tibshirani |
| 2021 | Convergence Properties of Stochastic Hypergradients. | Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo |
| 2021 | Follow Your Star: New Frameworks for Online Stochastic Matching with Known and Unknown Patience. | Nathaniel Grammel, Brian Brubach, Will Ma, Aravind Srinivasan |
| 2021 | SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation. | Robert M. Gower, Othmane Sebbouh, Nicolas Loizou |
| 2021 | Nested Barycentric Coordinate System as an Explicit Feature Map. | Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch, Ofir Pele |
| 2021 | Local SGD: Unified Theory and New Efficient Methods. | Eduard Gorbunov, Filip Hanzely, Peter Richtrik |
| 2021 | Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data. | Yu Gong, Hossein Hajimirsadeghi, Jiawei He, Thibaut Durand, Greg Mori |
| 2021 | Learning Smooth and Fair Representations. | Xavier Gitiaux, Huzefa Rangwala |
| 2021 | Shuffled Model of Differential Privacy in Federated Learning. | Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh |
| 2021 | Competing AI: How does competition feedback affect machine learning? | Tony Ginart, Eva Zhang, Yongchan Kwon, James Zou |
| 2021 | A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets. | Gauthier Gidel, David Balduzzi, Wojciech Czarnecki, Marta Garnelo, Yoram Bachrach |
| 2021 | Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits. | Avishek Ghosh, Abishek Sankararaman, Kannan Ramchandran |
| 2021 | Variational inference for nonlinear ordinary differential equations. | Sanmitra Ghosh, Paul Birrell, Daniela De Angelis |
| 2021 | Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model. | Nafiseh Ghoroghchian, Gautam Dasarathy, Stark C. Draper |
| 2021 | Robust and Private Learning of Halfspaces. | Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thao Nguyen |
| 2021 | Deep Generative Missingness Pattern-Set Mixture Models. | Sahra Ghalebikesabi, Rob Cornish, Chris C. Holmes, Luke J. Kelly |
| 2021 | LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads. | Hossein Shokri Ghadikolaei, Sebastian U. Stich, Martin Jaggi |