| 2026 | Recovery thresholds for hidden weighted sparse graphs (extended abstract). | Zhe Hou, Jingcheng Liu |
| 2026 | Uniform Laws of Large Numbers in Product Spaces. | Ron Holzman, Shay Moran, Alexander Shlimovich |
| 2026 | A Perfectly Truthful Calibration Measure. | Jason D. Hartline, Lunjia Hu, Yifan Wu |
| 2026 | Learning from Biased and Costly Data Sources: Minimax-optimal Data Collection under a Budget (extended abstract). | Michael O. Harding, Vikas Singh, Kirthevasan Kandasamy |
| 2026 | Price of metric universality in vector quantization is at most 0.11 bit. | Alina Harbuzova, Or Ordentlich, Yury Polyanskiy |
| 2026 | An Empirical Bayes Perspective on Heteroskedastic Mean Estimation. | Yanjun Han, Abhishek Shetty, Jacob Shkrob |
| 2026 | Is Multi-Distribution Learning as Easy as PAC Learning: Sharp Rates with Bounded Label Noise. | Rafael Hanashiro, Abhishek Shetty, Patrick Jaillet |
| 2026 | High Probability Convergence Guarantees of Stochastic Gradient Descent Ascent in Structured Nonconvex Min-Max Games. | Junsoo Ha |
| 2026 | Functional Stochastic Localization. | Anming Gu, Bobby Shi, Kevin Tian |
| 2026 | A Unified Lower Bound on the Noisy Query Complexity of Boolean Functions. | Yuzhou Gu, Xin Li, Yinzhan Xu |
| 2026 | Computing Lewis weights to high precision using local relative smoothness. | Sander Gribling, Aaron Sidford, Chenyi Zhang |
| 2026 | Online Convex Optimization with Sublinear Noisy Probes. | Simone Di Gregorio, Anupam Gupta, Stefano Leonardi, Matteo Russo |
| 2026 | Randomization for Faster Exact Optimization of Discounted Markov Decision Processes. | Andrei Graur, Aaron Sidford, Ta-Wei Tu |
| 2026 | Compact Geometric Representations of Hierarchies. | Prashant Gokhale, Piotr Indyk, Yuhao Liu, Sandeep Silwal, Tony Chang Wang, Haike Xu |
| 2026 | Testing Noise Assumptions of Learning Algorithms. | Surbhi Goel, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan |
| 2026 | Robust Algorithms for Finding Cliques in Random Intersection Graphs via Sum-of-Squares. | Andreas Gbel, Janosch Ruff, Leon Schiller |
| 2026 | Information-Theoretic Thresholds for Bipartite Latent-Space Graphs Under Noisy Observations. | Andreas Gbel, Marcus Pappik, Leon Schiller |
| 2026 | Sample-Efficient Omniprediction for Proper Losses. | Isaac Gibbs, Ryan J. Tibshirani |
| 2026 | On the Statistical Query Complexity of Learning Semiautomata: a Random Walk Approach. | George Giapitzakis, Kimon Fountoulakis, Eshaan Nichani, Jason D. Lee |
| 2026 | Universality of high-dimensional scaling limits of stochastic gradient descent (extended abstract). | Reza Gheissari, Aukosh Jagannath |
| 2026 | Nearly Linear-Time User-Level DP-SCO with Optimal Rates. | Badih Ghazi, Ravi Kumar, Daogao Liu, Pasin Manurangsi |
| 2026 | Fixed-Parameter Tractability of Private Synthetic Data Generation. | Badih Ghazi, Cristbal Guzmn, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi |
| 2026 | Fast and Large-Scale Unbalanced Optimal Transport via its Semi-Dual and Adaptive Gradient Methods. | Ferdinand Genans |
| 2026 | How Many Features Can a Language Model Store Under the Linear Representation Hypothesis? | Nikhil Garg, Jon M. Kleinberg, Kenny Peng |
| 2026 | Optimal Hardness of Online Algorithms for Large Common Induced Subgraphs. | David Gamarnik, Mikls Z. Rcz, Gabe Schoenbach |