:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhang, Yuhui, Wu, Dongshen, Wada, Yuichiro, Kanamori, Takafumi
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	https://arxiv.org/abs/2505.16923
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Robust VAEs via Generating Process of Noise Augmented Data
par: Irobe, Hiroo, et autres
Publié: (2024)

Mixture Proportion Estimation and Weakly-supervised Kernel Test for Conditional Independence
par: Hirose, Yushi, et autres
Publié: (2026)

Robust Estimation for Kernel Exponential Families with Smoothed Total Variation Distances
par: Kanamori, Takafumi, et autres
Publié: (2024)

A Convex Framework for Confounding Robust Inference
par: Ishikawa, Kei, et autres
Publié: (2023)

Distributional Spectral Diagnostics for Localizing Grokking Transitions
par: Wang, Ziyue, et autres
Publié: (2026)

Scaling-based Data Augmentation for Generative Models and its Theoretical Extension
par: Koike, Yoshitaka, et autres
Publié: (2024)

Knowledge Distillation with Adapted Weight
par: Wu, Sirong, et autres
Publié: (2025)

Uncertainty-Aware Distribution-to-Distribution Flow Matching for Scientific Imaging
par: Wu, Dongxia, et autres
Publié: (2026)

EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty
par: Li, Yuhui, et autres
Publié: (2024)

Investigating Self-Supervised Image Denoising with Denaturation
par: Waida, Hiroki, et autres
Publié: (2024)

Revisiting Random Weight Perturbation for Efficiently Improving Generalization
par: Li, Tao, et autres
Publié: (2024)

Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution Shifts
par: Bui, Ha Manh, et autres
Publié: (2023)

Sparse Additive Model Pruning for Order-Based Causal Structure Learning
par: Kanamori, Kentaro, et autres
Publié: (2026)

Self-Concordant Perturbations for Linear Bandits
par: Lévy, Lucas, et autres
Publié: (2025)

Perturbation-Induced Linearization: Constructing Unlearnable Data with Solely Linear Classifiers
par: Liu, Jinlin, et autres
Publié: (2026)

A Perturbation Approach to Unconstrained Linear Bandits
par: Jacobsen, Andrew, et autres
Publié: (2026)

Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization
par: de Mathelin, Antoine, et autres
Publié: (2023)

Uncertainty Estimation via Hyperspherical Confidence Mapping
par: Choi, Eunseo, et autres
Publié: (2026)

Calibrating LLM Judges: Linear Probes for Fast and Reliable Uncertainty Estimation
par: Radharapu, Bhaktipriya, et autres
Publié: (2025)

FW-Shapley: Real-time Estimation of Weighted Shapley Values
par: Panda, Pranoy, et autres
Publié: (2025)

Uncertainty Weighted Gradients for Model Calibration
par: Lin, Jinxu, et autres
Publié: (2025)

From Risk to Uncertainty: Generating Predictive Uncertainty Measures via Bayesian Estimation
par: Kotelevskii, Nikita, et autres
Publié: (2024)

Inducing Uncertainty on Open-Weight Models for Test-Time Privacy in Image Recognition
par: Ashiq, Muhammad H., et autres
Publié: (2025)

Uncertainty-Calibrated Test-Time Model Adaptation without Forgetting
par: Tan, Mingkui, et autres
Publié: (2024)

Adaptive Conformal Prediction via Bayesian Uncertainty Weighting for Hierarchical Healthcare Data
par: Shahbazi, Marzieh Amiri, et autres
Publié: (2026)

Learning Decision Trees and Forests with Algorithmic Recourse
par: Kanamori, Kentaro, et autres
Publié: (2024)

Algorithmic Recourse with Missing Values
par: Kanamori, Kentaro, et autres
Publié: (2023)

Separating Intrinsic Ambiguity from Estimation Uncertainty in Deep Generative Models for Linear Inverse Problems
par: Guo, Yuxin, et autres
Publié: (2026)

Stabilizing Linear Passive-Aggressive Online Learning with Weighted Reservoir Sampling
par: Wu, Skyler, et autres
Publié: (2024)

Weighted Sequential Bayesian Inference for Non-Stationary Linear Contextual Bandits
par: Werge, Nicklas, et autres
Publié: (2023)

WeiPer: OOD Detection using Weight Perturbations of Class Projections
par: Granz, Maximilian, et autres
Publié: (2024)

Density Uncertainty Layers for Reliable Uncertainty Estimation
par: Park, Yookoon, et autres
Publié: (2023)

Perturbation-Assisted Sample Synthesis: A Novel Approach for Uncertainty Quantification
par: Liu, Yifei, et autres
Publié: (2023)

MoreauPruner: Robust Pruning of Large Language Models against Weight Perturbations
par: Wang, Zixiao, et autres
Publié: (2024)

Adversarial Bandit Optimization with Globally Bounded Perturbations to Linear Losses
par: Cheng, Zhuoyu, et autres
Publié: (2026)

Conformal Uncertainty Indicator for Continual Test-Time Adaptation
par: Lyu, Fan, et autres
Publié: (2025)

Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation
par: Chen, Xuexin, et autres
Publié: (2024)

Statistical learnability of smooth boundaries via pairwise binary classification with deep ReLU networks
par: Waida, Hiroki, et autres
Publié: (2025)

Enhancing the Dynamic Range of Quantum Sensing via Quantum Circuit Learning
par: Kawaguchi, Hideaki, et autres
Publié: (2025)

From Weight Perturbation to Feature Attribution for Explaining Fully Connected Neural Networks
par: Lymperopoulos, Thodoris, et autres
Publié: (2026)