Papers
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.
Testing Noise Assumptions of Learning Algorithms
Surbhi Goel, Adam Klivans, Konstantinos Stavropoulos et al.
Information-Theoretic Thresholds for Bipartite Latent-Space Graphs Under Noisy Observations
Andreas Göbel, Marcus Pappik, Leon Schiller
Robust Algorithms for Finding Cliques in Random Intersection Graphs via Sum-of-Squares
Andreas Göbel, Janosch Ruff, Leon Schiller
Sample-Efficient Omniprediction for Proper Losses
Isaac Gibbs, Ryan J. Tibshirani
On the Statistical Query Complexity of Learning Semiautomata: a Random Walk Approach
George Giapitzakis, Kimon Fountoulakis, Eshaan Nichani et al.
Universality of high-dimensional scaling limits of stochastic gradient descent (extended abstract)
Reza Gheissari, Aukosh Jagannath
Fixed-Parameter Tractability of Private Synthetic Data Generation
Badih Ghazi, Cristóbal Guzmán, Pritish Kamath et al.