Papers
Low-Degree Method Fails to Predict Robust Subspace Recovery
He Jia, Aravindan Vijayaraghavan
Sharp analysis of linear ensemble sampling
David Janz, Arya Akhavan, Csaba Szepesvári
On the Importance of Randomization in Discriminative Feature Feedback
Valentio Iverson, Tosca Lechner, Sivan Sabato
Adversarial Learning in Games with Bandit Feedback: Logarithmic Pure-Strategy Maximin Regret
Shinji Ito, Haipeng Luo, Arnab Maiti et al.
On Randomized Algorithms in Online Strategic Classification
Chase Hutton, Adam Melrod, Han Shao
Simultaneous Blackwell Approachability and Applications to Multiclass Omniprediction
Lunjia Hu, Kevin Tian, Chutong Yang
Recovery of Planted Subgraphs
Wasim Huleihel
Almost Linear Convergence under Minimal Score Assumptions: Quantized Transition Diffusion
Xunpeng Huang, Yingyu Lin, Lijing Kuang et al.
Reconstructing Riemannian Metrics From Random Geometric Graphs
Han Huang, Pakawut Jiradilok, Elchanan Mossel
Wasserstein Policy Learning for Distributional Outcomes
Yiyan Huang, Cheuk Hang Leung, Qi Wu et al.
Efficient Swap Multicalibration of Elicitable Properties
Lunjia Hu, Haipeng Luo, Spandan Senapati et al.
Near-optimal Swap Regret Minimization for Convex Losses
Lunjia Hu, Jon Schneider, Yifan Wu
Recovery thresholds for hidden weighted sparse graphs (extended abstract)
Zhe Hou, Jingcheng Liu
Uniform Laws of Large Numbers in Product Spaces
Ron Holzman, Shay Moran, Alexander Shlimovich
A Perfectly Truthful Calibration Measure
Jason Hartline, Lunjia Hu, Yifan Wu
Learning from Biased and Costly Data Sources: Minimax-optimal Data Collection under a Budget (extended abstract)
Michael O. Harding, Vikas Singh, Kirthevasan Kandasamy
Price of metric universality in vector quantization is at most 0.11 bit
Alina Harbuzova, Or Ordentlich, Yury Polyanskiy
Is Multi-Distribution Learning as Easy as PAC Learning: Sharp Rates with Bounded Label Noise
Rafael Hanashiro, Abhishek Shetty, Patrick Jaillet
An Empirical Bayes Perspective on Heteroskedastic Mean Estimation
Yanjun Han, Abhishek Shetty, Jacob Shkrob
Functional Stochastic Localization
Anming Gu, Bobby Shi, Kevin Tian
A Unified Lower Bound on the Noisy Query Complexity of Boolean Functions
Yuzhou Gu, Xin Li, Yinzhan Xu
Computing Lewis weights to high precision using local relative smoothness
Sander Gribling, Aaron Sidford, Chenyi Zhang
Randomization for Faster Exact Optimization of Discounted Markov Decision Processes
Andrei Graur, Aaron Sidford, Ta-Wei Tu
Compact Geometric Representations of Hierarchies
Prashant Gokhale, Piotr Indyk, Yuhao Liu et al.