| 2025 | STOC | Adaptive and Oblivious Statistical Adversaries Are Equivalent. | Guy Blanc, Gregory Valiant |
| 2025 | STOC | A Generalized Trace Reconstruction Problem: Recovering a String of Probabilities. | Joey Rivkin, Gregory Valiant, Paul Valiant |
| 2024 | STOC | Near-Optimal Mean Estimation with Unknown, Heteroskedastic Variances. | Spencer Compton, Gregory Valiant |
| 2023 | ICML | One-sided Matrix Completion from Two Observations Per Row. | Steven Cao, Percy Liang, Gregory Valiant |
| 2023 | IJCAI | Efficient Convex Optimization Requires Superlinear Memory (Extended Abstract). | Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant |
| 2022 | COLT | Big-Step-Little-Step: Efficient Gradient Methods for Objectives with Multiple Scales. | Jonathan A. Kelner, Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant, Honglin Yuan |
| 2022 | COLT | Efficient Convex Optimization Requires Superlinear Memory. | Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant |
| 2021 | ACL | Beyond Laurel/Yanny: An Autoencoder-Enabled Search for Polyperceivable Audio. | Kartik Chandra, Chuma Kabaghe, Gregory Valiant |
| 2021 | AISTATS | Misspecification in Prediction Problems and Robustness via Improper Learning. | Annie Marsden, John C. Duchi, Gregory Valiant |
| 2021 | COLT | Exponential Weights Algorithms for Selective Learning. | Mingda Qiao, Gregory Valiant |
| 2021 | ICML | Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training. | Kai Sheng Tai, Peter Bailis, Gregory Valiant |
| 2021 | STOC | Stronger calibration lower bounds via sidestepping. | Mingda Qiao, Gregory Valiant |
| 2020 | AISTATS | Sublinear Optimal Policy Value Estimation in Contextual Bandits. | Weihao Kong, Emma Brunskill, Gregory Valiant |
| 2020 | COLT | Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process. | Guy Blanc, Neha Gupta, Gregory Valiant, Paul Valiant |
| 2020 | ICML | Sample Amplification: Increasing Dataset Size even when Learning is Impossible. | Brian Axelrod, Shivam Garg, Vatsal Sharan, Gregory Valiant |
| 2020 | ICML | On the Generalization Effects of Linear Transformations in Data Augmentation. | Sen Wu, Hongyang R. Zhang, Gregory Valiant, Christopher R |
| 2019 | CogSci | A Surprising Density of Illusionable Natural Speech. | Melody Y. Guan, Gregory Valiant |
| 2019 | COLT | A Theory of Selective Prediction. | Mingda Qiao, Gregory Valiant |
| 2019 | ICML | Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data. | Vatsal Sharan, Kai Sheng Tai, Peter Bailis, Gregory Valiant |
| 2019 | ICML | Equivariant Transformer Networks. | Kai Sheng Tai, Peter Bailis, Gregory Valiant |
| 2019 | ICML | Maximum Likelihood Estimation for Learning Populations of Parameters. | Ramya Korlakai Vinayak, Weihao Kong, Gregory Valiant, Sham M. Kakade |
| 2019 | STOC | Memory-sample tradeoffs for linear regression with small error. | Vatsal Sharan, Aaron Sidford, Gregory Valiant |
| 2018 | COLT | A Data Prism: Semi-verified learning in the small-alpha regime. | Michela Meister, Gregory Valiant |
| 2018 | KDD | Approximating the Spectrum of a Graph. | David Cohen-Steiner, Weihao Kong, Christian Sohler, Gregory Valiant |
| 2018 | SIGMOD | Sketching Linear Classifiers over Data Streams. | Kai Sheng Tai, Vatsal Sharan, Peter Bailis, Gregory Valiant |
| 2018 | STOC | Prediction with a short memory. | Vatsal Sharan, Sham M. Kakade, Percy Liang, Gregory Valiant |
| 2017 | ICML | Estimating the unseen from multiple populations. | Aditi Raghunathan, Gregory Valiant, James Zou |
| 2017 | ICML | Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use. | Vatsal Sharan, Gregory Valiant |
| 2017 | STOC | Learning from untrusted data. | Moses Charikar, Jacob Steinhardt, Gregory Valiant |
| 2016 | COLT | Memory, Communication, and Statistical Queries. | Jacob Steinhardt, Gregory Valiant, Stefan Wager |
| 2016 | ESA | Stochastic Streams: Sample Complexity vs. Space Complexity. | Michael S. Crouch, Andrew McGregor, Gregory Valiant, David P. Woodruff |
| 2016 | STOC | Instance optimal learning of discrete distributions. | Gregory Valiant, Paul Valiant |
| 2014 | FOCS | Satisfiability and Evolution. | Adi Livnat, Christos H. Papadimitriou, Aviad Rubinstein, Gregory Valiant, Andrew Wan |
| 2014 | FOCS | An Automatic Inequality Prover and Instance Optimal Identity Testing. | Gregory Valiant, Paul Valiant |
| 2014 | ICML | Least Squares Revisited: Scalable Approaches for Multi-class Prediction. | Alekh Agarwal, Sham M. Kakade, Nikos Karampatziakis, Le Song, Gregory Valiant |
| 2014 | ICML | Learning Polynomials with Neural Networks. | Alexandr Andoni, Rina Panigrahy, Gregory Valiant, Li Zhang |
| 2014 | SODA | Learning Sparse Polynomial Functions. | Alexandr Andoni, Rina Panigrahy, Gregory Valiant, Li Zhang |
| 2014 | SODA | Optimal Algorithms for Testing Closeness of Discrete Distributions. | Siu On Chan, Ilias Diakonikolas, Paul Valiant, Gregory Valiant |
| 2013 | SODA | Testing | Constantinos Daskalakis, Ilias Diakonikolas, Rocco A. Servedio, Gregory Valiant, Paul Valiant |
| 2012 | FOCS | Finding Correlations in Subquadratic Time, with Applications to Learning Parities and Juntas. | Gregory Valiant |
| 2011 | FOCS | The Power of Linear Estimators. | Gregory Valiant, Paul Valiant |
| 2011 | PODC | Incentive-compatible distributed greedy protocols. | Noam Nisan, Michael Schapira, Gregory Valiant, Aviv Zohar |
| 2011 | STOC | Estimating the unseen: an n/log(n)-sample estimator for entropy and support size, shown optimal via new CLTs. | Gregory Valiant, Paul Valiant |
| 2010 | FOCS | Settling the Polynomial Learnability of Mixtures of Gaussians. | Ankur Moitra, Gregory Valiant |
| 2010 | STOC | Efficiently learning mixtures of two Gaussians. | Adam Tauman Kalai, Ankur Moitra, Gregory Valiant |
| 2010 | SAGT | On Learning Algorithms for Nash Equilibria. | Constantinos Daskalakis, Rafael M. Frongillo, Christos H. Papadimitriou, George Pierrakos, Gregory Valiant |
| 2009 | PODS | Size and treewidth bounds for conjunctive queries. | Georg Gottlob, Stephanie Tien Lee, Gregory Valiant |
| 2009 | SODA | On the complexity of Nash equilibria of action-graph games. | Constantinos Daskalakis, Grant Schoenebeck, Gregory Valiant, Paul Valiant |
| 2008 | SODA | Designing networks with good equilibria. | Ho-Lin Chen, Tim Roughgarden, Gregory Valiant |