Cover Image

Uniform convergence of the smooth calibration error and its relationship with functional gradient

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Futami, Futoshi, Nitanda, Atsushi
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Information-theoretic Generalization Analysis for VQ-VAEs: A Role of Latent Variables
by: Futami, Futoshi, et al.
Published: (2025)

PAC-Bayes Analysis for Recalibration in Classification
by: Fujisawa, Masahiro, et al.
Published: (2024)

Information-Theoretic Generalization Bounds for Sequential Decision Making
by: Futami, Futoshi, et al.
Published: (2026)

Unified Approach for Weakly Supervised Multicalibration
by: Futami, Futoshi, et al.
Published: (2026)

Robust and Computationally Efficient Linear Contextual Bandits under Adversarial Corruption and Heavy-Tailed Noise
by: Tani, Naoto, et al.
Published: (2026)

$L_2$-Regularized Empirical Risk Minimization Guarantees Small Smooth Calibration Error
by: Fujisawa, Masahiro, et al.
Published: (2025)

Information-theoretic Generalization Analysis for Expected Calibration Error
by: Futami, Futoshi, et al.
Published: (2024)

Data-driven Projection Generation for Efficiently Solving Heterogeneous Quadratic Programming Problems
by: Iwata, Tomoharu, et al.
Published: (2025)

Improved Particle Approximation Error for Mean Field Neural Networks
by: Nitanda, Atsushi
Published: (2024)

Why is parameter averaging beneficial in SGD? An objective smoothing perspective
by: Nitanda, Atsushi, et al.
Published: (2023)

How Does Preconditioning Guide Feature Learning in Deep Neural Networks?
by: Yoshida, Kotaro, et al.
Published: (2025)

Alternating Diffusion for Proximal Sampling with Zeroth Order Queries
by: Takagi, Hirohane, et al.
Published: (2026)

Statistical Analysis of the Sinkhorn Iterations for Two-Sample Schrödinger Bridge Estimation
by: Maeda, Ibuki, et al.
Published: (2025)

Mirror Descent Policy Optimisation for Robust Constrained Markov Decision Processes
by: Bossens, David M., et al.
Published: (2025)

Propagation of Chaos for Mean-Field Langevin Dynamics and its Application to Model Ensemble
by: Nitanda, Atsushi, et al.
Published: (2025)

Towards a Unified Analysis of Neural Networks in Nonparametric Instrumental Variable Regression: Optimization and Generalization
by: Chen, Zonghao, et al.
Published: (2025)

Direct Distributional Optimization for Provable Alignment of Diffusion Models
by: Kawata, Ryotaro, et al.
Published: (2025)

Slowly Annealed Langevin Dynamics: Theory and Applications to Training-Free Guided Generation
by: Nitanda, Atsushi, et al.
Published: (2026)

Intrinsic Wasserstein Rates for Score-Based Generative Models on Smooth Manifolds
by: Fu, Guoji, et al.
Published: (2026)

Koopman-based generalization bound: New aspect for full-rank weights
by: Hashimoto, Yuka, et al.
Published: (2023)

SGD method for entropy error function with smoothing l0 regularization for neural networks
by: Nguyen, Trong-Tuan, et al.
Published: (2024)

Uniform convergence for Gaussian kernel ridge regression
by: Dommel, Paul, et al.
Published: (2025)

Uniform error bounds for quantized dynamical models
by: Metakalard, Abdelkader, et al.
Published: (2026)

Provable Benefit of Curriculum in Transformer Tree-Reasoning Post-Training
by: Bu, Dake, et al.
Published: (2025)

Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning
by: Bu, Dake, et al.
Published: (2024)

Practical estimation of the optimal classification error with soft labels and calibration
by: Ushio, Ryota, et al.
Published: (2025)

A policy gradient approach for optimization of smooth risk measures
by: Vijayan, Nithia, et al.
Published: (2022)

Provable In-Context Vector Arithmetic via Retrieving Task Concepts
by: Bu, Dake, et al.
Published: (2025)

DPRM: A Plug-in Doob h transform-induced Token-Ordering Module for Diffusion Language Models
by: Bu, Dake, et al.
Published: (2026)

Almost sure convergence rates of stochastic gradient methods under gradient domination
by: Weissmann, Simon, et al.
Published: (2024)

Spectral bandits for smooth graph functions
by: Valko, Michal, et al.
Published: (2026)

Debiased high-dimensional regression calibration for errors-in-variables log-contrast models
by: Zhao, Huali, et al.
Published: (2024)

Post-Training as Reweighting: A Stochastic View of Reasoning Trajectories in Language Models
by: Bu, Dake, et al.
Published: (2025)

Problem-dependent convergence bounds for randomized linear gradient compression
by: Flynn, Thomas, et al.
Published: (2024)

Local linear convergence of gradient methods for overparameterized Gaussian mixtures
by: Wang, Jingxing, et al.
Published: (2026)

Online learning of smooth functions on $\mathbb{R}$
by: Geneson, Jesse, et al.
Published: (2026)

Uniform-in-$N$ log-Sobolev inequality for the mean-field Langevin dynamics with convex energy
by: Chewi, Sinho, et al.
Published: (2024)

Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates
by: Mei, Jincheng, et al.
Published: (2025)

Global convergence of gradient descent for phase retrieval
by: Fougereux, Théodore, et al.
Published: (2024)

On the rate of convergence of an over-parametrized Transformer classifier learned by gradient descent
by: Kohler, Michael, et al.
Published: (2023)