| 2026 | On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA. | Syamantak Kumar, Shourya Pandey, Purnamrita Sarkar, Kevin Tian |
| 2026 | A Distribution Testing Approach to Clustering Distributions. | Gunjan Kumar, Yash Pote, Jonathan Scarlett |
| 2026 | Clipping the Price of Adaptivity at the Tail. | Itai Kreisler, Yair Carmon, Oliver Hinder |
| 2026 | Ambiguous Online Learning. | Vanessa Kosoy |
| 2026 | Overlap Analysis of the Shortest Path Problem: Local Search, Landscapes, and Franz-Parisi Potential. | Frederic Koehler, Joonhyung Shin |
| 2026 | Sandwiching Polynomials for Geometric Concepts with Low Intrinsic Dimension. | Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan |
| 2026 | Spectral Valleys and Sharp Failures in Greedy Determinant Maximization. | Rajiv Khanna |
| 2026 | Recursively Enumerably Representable Classes and Computable Versions of the Fundamental Theorem of Statistical Learning. | David Kattermann, Lothar Sebastian Krapp |
| 2026 | Fast, Parallel, Query-Efficient Binary Classification. | Ishani Karmarkar, Liam O'Carroll, Aaron Sidford |
| 2026 | Can SGD Select Good Fishermen? Local Convergence under Self-Selection Biases (Extended Abstract). | Alkis Kalavasis, Anay Mehrotra, Felix Zhou |
| 2026 | Ripple Mechanisms for Discrete and Private Statistics. | Matthew Joseph, Alex Kulesza, Yuyan Wang, Alexander Yu |
| 2026 | Avoiding exp(k | Tianyuan Jin, Heyang Zhao, Vincent Y. F. Tan, Quanquan Gu |
| 2026 | Low-Degree Method Fails to Predict Robust Subspace Recovery. | He Jia, Aravindan Vijayaraghavan |
| 2026 | Adaptive Matrix Online Learning through Smoothing with Guarantees for Nonsmooth Nonconvex Optimization. | Ruichen Jiang, Zakaria Mhammedi, Mehryar Mohri, Aryan Mokhtari |
| 2026 | Sharp analysis of linear ensemble sampling. | David Janz, Arya Akhavan, Csaba Szepesvri |
| 2026 | On the Importance of Randomization in Discriminative Feature Feedback. | Valentio Iverson, Tosca Lechner, Sivan Sabato |
| 2026 | Adversarial Learning in Games with Bandit Feedback: Logarithmic Pure-Strategy Maximin Regret. | Shinji Ito, Haipeng Luo, Arnab Maiti, Taira Tsuchiya, Yue Wu |
| 2026 | Simultaneous Blackwell Approachability and Applications to Multiclass Omniprediction. | Lunjia Hu, Kevin Tian, Chutong Yang |
| 2026 | On Randomized Algorithms in Online Strategic Classification. | Chase Hutton, Adam Melrod, Han Shao |
| 2026 | Near-optimal Swap Regret Minimization for Convex Losses. | Lunjia Hu, Jon Schneider, Yifan Wu |
| 2026 | Efficient Swap Multicalibration of Elicitable Properties. | Lunjia Hu, Haipeng Luo, Spandan Senapati, Vatsal Sharan |
| 2026 | Recovery of Planted Subgraphs. | Wasim Huleihel |
| 2026 | Wasserstein Policy Learning for Distributional Outcomes. | Yiyan Huang, Cheuk Hang Leung, Qi Wu, Zhiheng Zhang |
| 2026 | Almost Linear Convergence under Minimal Score Assumptions: Quantized Transition Diffusion. | Xunpeng Huang, Yingyu Lin, Nikki Lijing Kuang, Hanze Dong, Difan Zou, Yian Ma, Tong Zhang |
| 2026 | Reconstructing Riemannian Metrics From Random Geometric Graphs. | Han Huang, Pakawut Jiradilok, Elchanan Mossel |