:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Cheshire, James, Issartel, Yann
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2603.15336
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Active Bipartite Ranking with Smooth Posterior Distributions
by: Cheshire, James, et al.
Published: (2026)

Symmetry Guarantees Statistic Recovery in Variational Inference
by: Marks, Daniel, et al.
Published: (2026)

Pair-Matching: Links Prediction with Adaptive Queries
by: Giraud, Christophe, et al.
Published: (2019)

Efficient Evaluation of LLM Performance with Statistical Guarantees
by: Wu, Skyler, et al.
Published: (2026)

Exact Matrix Seriation through Mathematical Optimization: Stress and Effectiveness-Based Models
by: Blanco, Víctor, et al.
Published: (2025)

Efficient Techniques for Data Reconstruction, with Finite-Width Recovery Guarantees
by: Tansley, Edward, et al.
Published: (2026)

Contrastive Learning for Semi-Supervised Deep Regression with Generalized Ordinal Rankings from Spectral Seriation
by: Wang, Ce, et al.
Published: (2025)

A Recovery Guarantee for Sparse Neural Networks
by: Fridovich-Keil, Sara, et al.
Published: (2025)

Statistical Guarantees for Offline Domain Randomization
by: Fickinger, Arnaud, et al.
Published: (2025)

Local Linear Recovery Guarantee of Deep Neural Networks at Overparameterization
by: Zhang, Yaoyu, et al.
Published: (2024)

Convergence and Recovery Guarantees of Unsupervised Neural Networks for Inverse Problems
by: Buskulic, Nathan, et al.
Published: (2023)

Active Preference Learning for Ordering Items In- and Out-of-sample
by: Bergström, Herman, et al.
Published: (2024)

Statistical Guarantees for High-Dimensional Stochastic Gradient Descent
by: Li, Jiaqi, et al.
Published: (2025)

Guaranteed Recovery of Unambiguous Clusters
by: Mazooji, Kayvon, et al.
Published: (2025)

Recovery Guarantees of Unsupervised Neural Networks for Inverse Problems trained with Gradient Descent
by: Buskulic, Nathan, et al.
Published: (2024)

Guaranteed Nonconvex Factorization Approach for Tensor Train Recovery
by: Qin, Zhen, et al.
Published: (2024)

Statistical Guarantees in the Search for Less Discriminatory Algorithms
by: Hays, Chris, et al.
Published: (2025)

Provably Efficient Off-Policy Adversarial Imitation Learning with Convergence Guarantees
by: Chen, Yilei, et al.
Published: (2024)

Active Statistical Inference
by: Zrnic, Tijana, et al.
Published: (2024)

Model-agnostic Selective Labeling with Provable Statistical Guarantees
by: Huang, Huipeng, et al.
Published: (2025)

Statistical Learning Guarantees for Group-Invariant Barron Functions
by: Yang, Yahong, et al.
Published: (2025)

Statistical Inference Leveraging Synthetic Data with Distribution-Free Guarantees
by: Bashari, Meshi, et al.
Published: (2025)

Certainty in Uncertainty: Reasoning over Uncertain Knowledge Graphs with Statistical Guarantees
by: Zhu, Yuqicheng, et al.
Published: (2025)

Differentially Private Linear Regression and Synthetic Data Generation with Statistical Guarantees
by: Lin, Shurong, et al.
Published: (2025)

A Recovery Theory for Diffusion Priors: Deterministic Analysis of the Implicit Prior Algorithm
by: Leong, Oscar, et al.
Published: (2025)

Sequential Audit Sampling with Statistical Guarantees
by: Kato, Masahiro, et al.
Published: (2026)

Efficient Unlearning with Privacy Guarantees
by: Domingo-Ferrer, Josep, et al.
Published: (2025)

Statistical Guarantees in Synthetic Data through Conformal Adversarial Generation
by: Vishwakarma, Rahul, et al.
Published: (2025)

Conformal Segmentation in Industrial Surface Defect Detection with Statistical Guarantees
by: Shen, Cheng, et al.
Published: (2025)

Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances
by: Wang, Jie, et al.
Published: (2024)

Statistical Guarantees for Approximate Stationary Points of Shallow Neural Networks
by: Taheri, Mahsa, et al.
Published: (2022)

Sharp Global Guarantees for Nonconvex Low-rank Recovery in the Noisy Overparameterized Regime
by: Zhang, Richard Y.
Published: (2021)

Riemannian Optimization for Non-convex Euclidean Distance Geometry with Global Recovery Guarantees
by: Smith, Chandler, et al.
Published: (2024)

Statistical Guarantees for Distributionally Robust Optimization with Optimal Transport and OT-Regularized Divergences
by: Birrell, Jeremiah, et al.
Published: (2026)

Learning U-Statistics with Active Inference
by: Wang, Xiaoning, et al.
Published: (2026)

Robust Sampling for Active Statistical Inference
by: Li, Puheng, et al.
Published: (2025)

Reliable Statistical Guarantees for Conformal Predictors with Small Datasets
by: Sánchez-Domínguez, Miguel, et al.
Published: (2025)

Active Learning for Decision Trees with Provable Guarantees
by: Moakhar, Arshia Soltani, et al.
Published: (2026)

Statistical Guarantees of Group-Invariant GANs
by: Chen, Ziyu, et al.
Published: (2023)

Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery
by: Giampouras, Paris, et al.
Published: (2024)