:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Dirksen, Sjoerd, Finke, Patrick, Genzel, Martin
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Statistics Theory
Online Access:	https://arxiv.org/abs/2310.00327
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Tuning-free one-bit covariance estimation using data-driven dithering
by: Dirksen, Sjoerd, et al.
Published: (2023)

Worst-Case Optimal Multi-Armed Gaussian Best Arm Identification with a Fixed Budget
by: Kato, Masahiro
Published: (2023)

Approximating Langevin Monte Carlo with ResNet-like Neural Network architectures
by: Miranda, Charles, et al.
Published: (2023)

Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces
by: Lyu, Yang, et al.
Published: (2025)

Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories
by: Zhang, Haobo, et al.
Published: (2024)

Near-optimal estimates for the $\ell^p$-Lipschitz constants of deep random ReLU neural networks
by: Dirksen, Sjoerd, et al.
Published: (2025)

Beyond ECE: Calibrated Size Ratio, Risk Assessment, and Confidence-Weighted Metrics
by: Martin-Maroto, Fernando, et al.
Published: (2026)

Nonparametric Factor Analysis and Beyond
by: Zheng, Yujia, et al.
Published: (2025)

Component-based Sketching for Deep ReLU Nets
by: Wang, Di, et al.
Published: (2024)

Mathematics of statistical sequential decision-making: concentration, risk-awareness and modelling in stochastic bandits, with applications to bariatric surgery
by: Saux, Patrick
Published: (2024)

Beyond Scores: Proximal Diffusion Models
by: Fang, Zhenghan, et al.
Published: (2025)

Beyond Benign Overfitting in Nadaraya-Watson Interpolators
by: Barzilai, Daniel, et al.
Published: (2025)

Active Learning via Regression Beyond Realizability
by: Ganju, Atul, et al.
Published: (2025)

Branch Scaling Manifests as Implicit Architectural Regularization for Improving Generalization in Overparameterized ResNets
by: Yu, Zixiong, et al.
Published: (2024)

Minimax Statistical Estimation under Wasserstein Contamination
by: Chao, Patrick, et al.
Published: (2023)

Asymptotics of Random Feature Regression Beyond the Linear Scaling Regime
by: Hu, Hong, et al.
Published: (2024)

Iterative Reweighted Framework Based Algorithms for Sparse Linear Regression with Generalized Elastic Net Penalty
by: Ding, Yanyun, et al.
Published: (2024)

Provable FDR Control for Deep Feature Selection: Deep MLPs and Beyond
by: Sawaya, Kazuma
Published: (2025)

Beyond Consistency: Inference for the Relative risk functional in Deep Nonparametric Cox Models
by: Ghosal, Sattwik, et al.
Published: (2026)

Sharp Risk Bounds for Early-Stopping in Gaussian Linear Regression
by: Wegel, Tobias, et al.
Published: (2025)

Beyond Sin-Squared Error: Linear-Time Entrywise Uncertainty Quantification for Streaming PCA
by: Kumar, Syamantak, et al.
Published: (2025)

Beyond Uncertainty Sets: Leveraging Optimal Transport to Extend Conformal Predictive Distribution to Multivariate Settings
by: Ndiaye, Eugene
Published: (2025)

Sequential Bayesian Neural Subnetwork Ensembles
by: Jantre, Sanket, et al.
Published: (2022)

Approximation of RKHS Functionals by Neural Networks
by: Zhou, Tian-Yi, et al.
Published: (2024)

Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions
by: Zhang, Kaihong, et al.
Published: (2024)

Implicit Regularization Paths of Weighted Neural Representations
by: Du, Jin-Hong, et al.
Published: (2024)

Consistency for Large Neural Networks: Regression and Classification
by: Zhan, Haoran, et al.
Published: (2024)

Phase Transitions for Feature Learning in Neural Networks
by: Montanari, Andrea, et al.
Published: (2026)

A Unified Framework for Pattern Recovery in Penalized and Thresholded Estimation and its Geometry
by: Graczyk, Piotr, et al.
Published: (2023)

Implicit Regularisation in Diffusion Models: An Algorithm-Dependent Generalisation Analysis
by: Farghly, Tyler, et al.
Published: (2025)

Adaptive Lasso, Transfer Lasso, and Beyond: An Asymptotic Perspective
by: Takada, Masaaki, et al.
Published: (2023)

Affine Invariance in Continuous-Domain Convolutional Neural Networks
by: Mohaddes, Ali, et al.
Published: (2023)

Can Bayesian Neural Networks Make Confident Predictions?
by: Fisher, Katharine, et al.
Published: (2025)

Tensor Product Neural Networks for Functional ANOVA Model
by: Park, Seokhun, et al.
Published: (2025)

Structural Foundations for Leading Digit Laws: Beyond Probabilistic Mixtures
by: Berman, Vladimir
Published: (2025)

Exploring the Complexity of Deep Neural Networks through Functional Equivalence
by: Shen, Guohao
Published: (2023)

Dense ReLU Neural Networks for Temporal-spatial Model
by: Padilla, Carlos Misael Madrid, et al.
Published: (2024)

Non-identifiability distinguishes Neural Networks among Parametric Models
by: Chatterjee, Sourav, et al.
Published: (2025)

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

Inference for Deep Neural Network Estimators in Generalized Nonparametric Models
by: Meng, Xuran, et al.
Published: (2025)