Sparsified-Learning for High-Dimensional Heavy-Tailed Locally Stationary Time Series, Concentration and Oracle Inequalities
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Yingjie, Alaya, Mokhtar Z., Bouzebda, Salim, Liu, Xinsheng |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Bounds in Wasserstein Distance for Locally Stationary Functional Time Series
by: Tinio, Jan Nino G., et al.
Published: (2025)
by: Tinio, Jan Nino G., et al.
Published: (2025)
Bounds in Wasserstein Distance for Locally Stationary Processes
by: Tinio, Jan Nino G., et al.
Published: (2024)
by: Tinio, Jan Nino G., et al.
Published: (2024)
A Unified Kantorovich Duality for Multimarginal Optimal Transport
by: Cheryala, Yehya, et al.
Published: (2026)
by: Cheryala, Yehya, et al.
Published: (2026)
Gaussian-Smoothed Sliced Probability Divergences
by: Alaya, Mokhtar Z., et al.
Published: (2024)
by: Alaya, Mokhtar Z., et al.
Published: (2024)
A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers
by: He, Ye, et al.
Published: (2024)
by: He, Ye, et al.
Published: (2024)
Inference for Non-Stationary Heavy Tailed Time Series
by: Akashi, Fumiya, et al.
Published: (2022)
by: Akashi, Fumiya, et al.
Published: (2022)
Sharp Concentration Inequalities: Phase Transition and Mixing of Orlicz Tails with Variance
by: Shen, Yinan, et al.
Published: (2026)
by: Shen, Yinan, et al.
Published: (2026)
Asymptotic Classification Error for Heavy-Tailed Renewal Processes
by: Rong, Xinhui, et al.
Published: (2024)
by: Rong, Xinhui, et al.
Published: (2024)
Concentration of the Langevin Algorithm's Stationary Distribution
by: Altschuler, Jason M., et al.
Published: (2022)
by: Altschuler, Jason M., et al.
Published: (2022)
Sparse Tucker Decomposition and Graph Regularization for High-Dimensional Time Series Forecasting
by: Xia, Sijia, et al.
Published: (2026)
by: Xia, Sijia, et al.
Published: (2026)
On Statistical Inference for High-Dimensional Binary Time Series
by: Dai, Dehao, et al.
Published: (2025)
by: Dai, Dehao, et al.
Published: (2025)
Diffusion Models with Heavy-Tailed Targets: Score Estimation and Sampling Guarantees
by: Yu, Yifeng, et al.
Published: (2026)
by: Yu, Yifeng, et al.
Published: (2026)
From Spikes to Heavy Tails: Unveiling the Spectral Evolution of Neural Networks
by: Kothapalli, Vignesh, et al.
Published: (2024)
by: Kothapalli, Vignesh, et al.
Published: (2024)
A Simple and Optimal Policy Design with Safety against Heavy-Tailed Risk for Stochastic Bandits
by: Simchi-Levi, David, et al.
Published: (2022)
by: Simchi-Levi, David, et al.
Published: (2022)
The Price of Sparsity: Sufficient Conditions for Sparse Recovery using Sparse and Sparsified Measurements
by: Chaabouni, Youssef, et al.
Published: (2025)
by: Chaabouni, Youssef, et al.
Published: (2025)
A nonparametric distribution-free test of independence among continuous random vectors based on \texorpdfstring{$L_1$}{}-norm
by: Berrahou, Nour-Eddine, et al.
Published: (2021)
by: Berrahou, Nour-Eddine, et al.
Published: (2021)
A Uniform Concentration Inequality for Kernel-Based Two-Sample Statistics
by: Ni, Yijin, et al.
Published: (2024)
by: Ni, Yijin, et al.
Published: (2024)
Finite-Sample Wasserstein Error Bounds and Concentration Inequalities for Nonlinear Stochastic Approximation
by: Kong, Seo Taek, et al.
Published: (2026)
by: Kong, Seo Taek, et al.
Published: (2026)
High-accuracy and dimension-free sampling with diffusions
by: Gatmiry, Khashayar, et al.
Published: (2026)
by: Gatmiry, Khashayar, et al.
Published: (2026)
Privacy of SGD under Gaussian or Heavy-Tailed Noise: Guarantees without Gradient Clipping
by: Şimşekli, Umut, et al.
Published: (2024)
by: Şimşekli, Umut, et al.
Published: (2024)
Transfer Learning for Benign Overfitting in High-Dimensional Linear Regression
by: Kim, Yeichan, et al.
Published: (2025)
by: Kim, Yeichan, et al.
Published: (2025)
Adaptive Smooth Non-Stationary Bandits
by: Suk, Joe
Published: (2024)
by: Suk, Joe
Published: (2024)
Transfer Learning and Locally Linear Regression for Locally Stationary Time Series
by: Park, Jinwoo
Published: (2025)
by: Park, Jinwoo
Published: (2025)
Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting
by: Hasson, Hilaf, et al.
Published: (2023)
by: Hasson, Hilaf, et al.
Published: (2023)
Minimax Rate-Optimal Algorithms for High-Dimensional Stochastic Linear Bandits
by: Liu, Jingyu, et al.
Published: (2025)
by: Liu, Jingyu, et al.
Published: (2025)
Sampling from the Mean-Field Stationary Distribution
by: Kook, Yunbum, et al.
Published: (2024)
by: Kook, Yunbum, et al.
Published: (2024)
A Generalized Adaptive Joint Learning Framework for High-Dimensional Time-Varying Models
by: Chen, Baolin, et al.
Published: (2026)
by: Chen, Baolin, et al.
Published: (2026)
DeepLévy: Learning Heavy-Tailed Uncertainty in Highly Volatile Time Series
by: Yang, Yang, et al.
Published: (2026)
by: Yang, Yang, et al.
Published: (2026)
Factor Augmented High-Dimensional SGD
by: Li, Shubo, et al.
Published: (2026)
by: Li, Shubo, et al.
Published: (2026)
Inferring Change Points in High-Dimensional Regression via Approximate Message Passing
by: Arpino, Gabriel, et al.
Published: (2024)
by: Arpino, Gabriel, et al.
Published: (2024)
Sign Identifiability of Causal Effects in Stationary Stochastic Dynamical Systems
by: van Seeventer, Gijs, et al.
Published: (2026)
by: van Seeventer, Gijs, et al.
Published: (2026)
Statistical Guarantees for Approximate Stationary Points of Shallow Neural Networks
by: Taheri, Mahsa, et al.
Published: (2022)
by: Taheri, Mahsa, et al.
Published: (2022)
Topological Analysis for Detecting Anomalies (TADA) in Time Series
by: Chazal, Frédéric, et al.
Published: (2024)
by: Chazal, Frédéric, et al.
Published: (2024)
Navigating Sparsities in High-Dimensional Linear Contextual Bandits
by: Zhao, Rui, et al.
Published: (2025)
by: Zhao, Rui, et al.
Published: (2025)
Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems
by: Puchkin, Nikita, et al.
Published: (2023)
by: Puchkin, Nikita, et al.
Published: (2023)
Kernel-based Optimally Weighted Conformal Time-Series Prediction
by: Lee, Jonghyeok, et al.
Published: (2024)
by: Lee, Jonghyeok, et al.
Published: (2024)
ResCP: Reservoir Conformal Prediction for Time Series Forecasting
by: Neglia, Roberto, et al.
Published: (2025)
by: Neglia, Roberto, et al.
Published: (2025)
Benign Overfitting in Time Series Linear Models with Over-Parameterization
by: Nakakita, Shogo, et al.
Published: (2022)
by: Nakakita, Shogo, et al.
Published: (2022)
High-Dimensional Importance-Weighted Information Criteria: Theory and Optimality
by: Cao, Yong-Syun, et al.
Published: (2025)
by: Cao, Yong-Syun, et al.
Published: (2025)
Optimizing High-Dimensional Oblique Splits
by: Chi, Chien-Ming
Published: (2025)
by: Chi, Chien-Ming
Published: (2025)
Similar Items
-
Bounds in Wasserstein Distance for Locally Stationary Functional Time Series
by: Tinio, Jan Nino G., et al.
Published: (2025) -
Bounds in Wasserstein Distance for Locally Stationary Processes
by: Tinio, Jan Nino G., et al.
Published: (2024) -
A Unified Kantorovich Duality for Multimarginal Optimal Transport
by: Cheryala, Yehya, et al.
Published: (2026) -
Gaussian-Smoothed Sliced Probability Divergences
by: Alaya, Mokhtar Z., et al.
Published: (2024) -
A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers
by: He, Ye, et al.
Published: (2024)