:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Karki, Jony, Huang, Dongzhou, Zhao, Yunpeng
Format:	Preprint
Published:	2025
Subjects:	Machine Learning 62F12
Online Access:	https://arxiv.org/abs/2511.17783
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Differentiable Interacting Multiple Model Particle Filtering
by: Brady, John-Joseph, et al.
Published: (2024)

The Bernstein-von Mises theorem for Bayesian one-pass online learning
by: Lee, Jeyong, et al.
Published: (2026)

Asymptotic Theory for Graphical SLOPE: Precision Estimation and Pattern Convergence
by: Hejný, Ivan, et al.
Published: (2026)

Statistical Inference with Stochastic Gradient Methods under $ϕ$-mixing Data
by: Liu, Ruiqi, et al.
Published: (2023)

On Bayesian Softmax-Gated Mixture-of-Experts Models
by: Bariletto, Nicola, et al.
Published: (2026)

Simultaneous Heterogeneity and Reduced-rank Learning for Multivariate Response Regression
by: Wu, Jie, et al.
Published: (2025)

Dimension-free uniform concentration bound for logistic regression
by: Nakakita, Shogo
Published: (2024)

MIBoost: A gradient boosting algorithm for variable selection after multiple imputation
by: Kuchen, Robert
Published: (2025)

Learning Against Distributional Uncertainty: On the Trade-off Between Robustness and Specificity
by: Wang, Shixiong, et al.
Published: (2023)

Distributional Robustness Bounds Generalization Errors
by: Wang, Shixiong, et al.
Published: (2022)

Universal Lower Bounds and Optimal Rates: Achieving Minimax Clustering Error in Sub-Exponential Mixture Models
by: Dreveton, Maximilien, et al.
Published: (2024)

From Tail Universality to Bernstein-von Mises: A Unified Statistical Theory of Semi-Implicit Variational Inference
by: Plummer, Sean
Published: (2025)

DecoR: Deconfounding Time Series with Robust Regression
by: Schur, Felix, et al.
Published: (2024)

Amortized Variational Inference for Logistic Regression with Missing Covariates
by: Cherifi, M., et al.
Published: (2026)

Differentiable Calibration of Inexact Stochastic Simulation Models via Kernel Score Minimization
by: Su, Ziwei, et al.
Published: (2024)

Moment-Based Inference for Regression with Latent Dirichlet Covariates
by: Jiang, Ziyu
Published: (2026)

Mixed Semi-Supervised Generalized-Linear-Regression with Applications to Deep-Learning and Interpolators
by: Yuval, Oren, et al.
Published: (2023)

Near optimal sample complexity for matrix and tensor normal models via geodesic convexity
by: Franks, Cole, et al.
Published: (2021)

Bayesian inference with sources of uncertainty: from confidence modelling to sparse estimation
by: Rosa, Rafael Mouallem, et al.
Published: (2026)

Inference for high-dimensional linear expectile regression with de-biased method
by: Li, Xiang, et al.
Published: (2024)

Asymptotics of Stochastic Gradient Descent with Dropout Regularization in Linear Models
by: Li, Jiaqi, et al.
Published: (2024)

Wasserstein-Cramér-Rao Theory of Unbiased Estimation
by: Trillos, Nicolás García, et al.
Published: (2025)

Shrinkage to Infinity: Reducing Test Error by Inflating the Minimum Norm Interpolator in Linear Models
by: Freeman, Jake
Published: (2025)

Fused Multinomial Logistic Regression Utilizing Summary-Level External Machine-learning Information
by: Dai, Chi-Shian, et al.
Published: (2026)

Statistical Inference for Low-Rank Tensor Models
by: Xu, Ke, et al.
Published: (2025)

Almost exact recovery in noisy semi-supervised learning
by: Avrachenkov, Konstantin, et al.
Published: (2020)

When Does Dynamic Preconditioning Preserve the Polyak-Ruppert CLT? A Stabilization Threshold
by: An, Sunyoung, et al.
Published: (2026)

Laplace Variational Inference for Bayesian Envelope Models
by: Kim, Seunghyeon, et al.
Published: (2026)

Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation
by: Tan, Hong Ye, et al.
Published: (2024)

Higher-Order Equilibrium Tracking for EM-Compressible Online Estimation
by: Li, ZhiMing, et al.
Published: (2026)

Mixture of segmentation for heterogeneous functional data
by: Brault, Vincent, et al.
Published: (2023)

K-Means as a Radial Basis function Network: a Variational and Gradient-based Equivalence
by: Arredondo, Felipe de Jesus Felix, et al.
Published: (2026)

Fixed-Horizon Self-Normalized Inference for Adaptive Experiments via Martingale AIPW/DML with Logged Propensities
by: Saco, Gabriel
Published: (2026)

Estimation Method under Three-Parameter Generalized Exponential Model: Consistency, Uniqueness and its Applications
by: Prajapat, Kiran, et al.
Published: (2024)

Bayesian Inference for Left-Truncated Log-Logistic Distributions for Time-to-event Data Analysis
by: Mostafa, Fahad, et al.
Published: (2025)

Multivariate MM-estimators with auxiliary Scale for Linear Models with Structured Covariance Matrices
by: Lopuhaa, Hendrik Paul
Published: (2025)

A2 Copula-Driven Spatial Bayesian Neural Network For Modeling Non-Gaussian Dependence: A Simulation Study
by: Aich, Agnideep, et al.
Published: (2025)

Diagonally-Weighted Generalized Method of Moments Estimation for Gaussian Mixture Modeling
by: Zhang, Liu, et al.
Published: (2025)

A Novel Theoretical Framework for Exponential Smoothing
by: Bernardi, Enrico, et al.
Published: (2024)

Improved estimators in Bell regression model with application
by: Seifollahi, Solmaz, et al.
Published: (2024)