:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Jiang, Hangjin, Li, Yuzhou, Gao, Zhaoxing
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2601.11091
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Regularized Estimation of High-Dimensional Matrix-Variate Autoregressive Models
by: Jiang, Hangjin, et al.
Published: (2024)

Sparse Asymptotic PCA: Identifying Sparse Latent Factors Across Time Horizon in High-Dimensional Time Series
by: Gao, Zhaoxing
Published: (2024)

Denoising and Multilinear Projected-Estimation of High-Dimensional Matrix-Variate Factor Time Series
by: Gao, Zhaoxing, et al.
Published: (2023)

Modeling High-Dimensional Dependent Data in the Presence of Many Explanatory Variables and Weak Signals
by: Gao, Zhaoxing, et al.
Published: (2024)

High-Dimensional Matrix-Variate Diffusion Index Models for Time Series Forecasting
by: Ma, Zhiren, et al.
Published: (2025)

Optimal Bias-Correction and Valid Inference in High-Dimensional Ridge Regression: A Closed-Form Solution
by: Gao, Zhaoxing, et al.
Published: (2024)

TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time Series Forecasting
by: Kong, Linghang, et al.
Published: (2024)

Split and Conquer Partial Deepfake Speech
by: Rimon, Inbal, et al.
Published: (2026)

Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization
by: Liu, Yirui, et al.
Published: (2023)

Unified Sparse-Matrix Representations for Diverse Neural Architectures
by: Zhu, Yuzhou
Published: (2025)

Quasicrystal Architected Nanomechanical Resonators via Data-Driven Design
by: Li, Kawen, et al.
Published: (2026)

Accurate and Scalable Matrix Mechanisms via Divide and Conquer
by: He, Guanlin, et al.
Published: (2026)

Nonnegative Matrix Factorization in Dimensionality Reduction: A Survey
by: Saberi-Movahed, Farid, et al.
Published: (2024)

Adaptive Long-Run Variance Thresholding for Sparse Covariance Estimation in High-Dimensional Time Series
by: Zhang, Wenhao, et al.
Published: (2026)

Online Graph Topology Learning from Matrix-valued Time Series
by: Jiang, Yiye, et al.
Published: (2021)

On Sparse High-Dimensional Graphical Model Learning For Dependent Time Series
by: Tugnait, Jitendra K.
Published: (2021)

Spectral Differential Network Analysis for High-Dimensional Time Series
by: Hellstern, Michael, et al.
Published: (2024)

Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time
by: Gu, Yuzhou, et al.
Published: (2023)

Optimizing High-Dimensional Oblique Splits
by: Chi, Chien-Ming
Published: (2025)

An Interpretable and Efficient Infinite-Order Vector Autoregressive Model for High-Dimensional Time Series
by: Zheng, Yao
Published: (2022)

VE: Modeling Multivariate Time Series Correlation with Variate Embedding
by: Wang, Shangjiong, et al.
Published: (2024)

On Statistical Inference for High-Dimensional Binary Time Series
by: Dai, Dehao, et al.
Published: (2025)

A Divide-and-Conquer Approach for Modeling Arrival Times in Business Process Simulation
by: Kirchdorfer, Lukas, et al.
Published: (2025)

Unicorn: Scaling High-Dimensional Time Series Forecasting via Universal Correlation Modeling
by: Yuan, Haochen, et al.
Published: (2026)

An Interpretable Generative Framework for Anomaly Detection in High-Dimensional Financial Time Series
by: Martinez, Waldyn G
Published: (2026)

U-Cast: Learning Hierarchical Structures for High-Dimensional Time Series Forecasting
by: Ni, Juntong, et al.
Published: (2025)

Hypothesis Testing for High-Dimensional Matrix-Valued Data
by: Cui, Shijie, et al.
Published: (2024)

Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling
by: Yu, Guoqi, et al.
Published: (2024)

Doubly Non-Central Beta Matrix Factorization for Stable Dimensionality Reduction of Bounded Support Matrix Data
by: Albert, Anjali N., et al.
Published: (2024)

Machine Learning-Assisted High-Dimensional Matrix Estimation
by: Tian, Wan, et al.
Published: (2026)

Factor Augmented High-Dimensional SGD
by: Li, Shubo, et al.
Published: (2026)

Variable Splitting Binary Tree Models Based on Bayesian Context Tree Models for Time Series Segmentation
by: Nakahara, Yuta, et al.
Published: (2026)

A Supervised Screening and Regularized Factor-Based Method for Time Series Forecasting
by: Tu, Sihan, et al.
Published: (2025)

Distribution Agnostic Symbolic Representations for Time Series Dimensionality Reduction and Online Anomaly Detection
by: Bountrogiannis, Konstantinos, et al.
Published: (2021)

Effectiveness of High-Dimensional Distance Metrics on Solar Flare Time Series
by: Rohlfing, Elaina, et al.
Published: (2025)

Explain Variance of Prediction in Variational Time Series Models for Clinical Deterioration Prediction
by: Liu, Jiacheng, et al.
Published: (2024)

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models
by: Ge, Yunfeng, et al.
Published: (2025)

Sparse Tucker Decomposition and Graph Regularization for High-Dimensional Time Series Forecasting
by: Xia, Sijia, et al.
Published: (2026)

Model-Estimation-Free, Dense, and High Dimensional Consistent Precision Matrix Estimators
by: Stojnic, Mehmet Caner Agostino Capponi Mihailo
Published: (2025)

Inverting the Leverage Score Gradient: An Efficient Approximate Newton Method
by: Li, Chenyang, et al.
Published: (2024)