Cover Image

Learning Sparse High-Dimensional Matrix-Valued Graphical Models From Dependent Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Tugnait, Jitendra K
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Signal Processing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Learning Conditional Independence Differential Graphs From Time-Dependent Data
by: Tugnait, Jitendra K
Published: (2025)

On Conditional Independence Graph Learning From Multi-Attribute Gaussian Dependent Time Series
by: Tugnait, Jitendra K.
Published: (2025)

Multi-Attribute Graph Estimation with Sparse-Group Non-Convex Penalties
by: Tugnait, Jitendra K
Published: (2025)

Learning Multi-Attribute Differential Graphs with Non-Convex Penalties
by: Tugnait, Jitendra K
Published: (2025)

Robust Sparse Bayesian Learning Based on Minimum Error Entropy for Noisy High-Dimensional Brain Activity Decoding
by: Li, Yuanhao, et al.
Published: (2025)

Sparse Graph Learning from Sparse Data via Fiedler Number Maximization
by: Oveisgharan, Bahar, et al.
Published: (2026)

Nonnegative Matrix Factorization in the Component-Wise L1 Norm for Sparse Data
by: Seraghiti, Giovanni, et al.
Published: (2026)

Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior
by: Navarro, Madeline, et al.
Published: (2024)

Including Node Textual Metadata in Laplacian-constrained Gaussian Graphical Models
by: Wang, Jianhua, et al.
Published: (2026)

Polynomial Graphical Lasso: Learning Edges from Gaussian Graph-Stationary Signals
by: Buciulea, Andrei, et al.
Published: (2024)

Learning the Influence Graph of a High-Dimensional Markov Process with Memory
by: Bagewadi, Smita, et al.
Published: (2024)

Explicit Group Sparse Projection with Applications to Deep Learning and NMF
by: Ohib, Riyasat, et al.
Published: (2019)

Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems
by: Lin, Zhidi, et al.
Published: (2025)

Transferable Graphical MARL for Real-Time Estimation in Dynamic Wireless Networks
by: Chen, Xingran, et al.
Published: (2024)

Deep Variational Sequential Monte Carlo for High-Dimensional Observations
by: van Nierop, Wessel L., et al.
Published: (2025)

Enhancing Off-Grid One-Bit DOA Estimation with Learning-Based Sparse Bayesian Approach for Non-Uniform Sparse Array
by: Hu, Yunqiao, et al.
Published: (2024)

Algorithms for Non-Negative Matrix Factorization on Noisy Data With Negative Values
by: Green, Dylan, et al.
Published: (2023)

Load Forecasting on A Highly Sparse Electrical Load Dataset Using Gaussian Interpolation
by: Biswas, Chinmoy, et al.
Published: (2025)

High-Dimensional Confidence Regions in Sparse MRI
by: Hoppe, Frederik, et al.
Published: (2024)

Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming
by: Yokota, Haruki, et al.
Published: (2025)

Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements
by: Jenkins, Alexander, et al.
Published: (2025)

Downlink Channel Covariance Matrix Estimation via Representation Learning with Graph Regularization
by: Zerin, Melih Can, et al.
Published: (2024)

Nonparametric Bellman Mappings for Value Iteration in Distributed Reinforcement Learning
by: Akiyama, Yuki, et al.
Published: (2025)

Hierarchical Decomposed Dual-domain Deep Learning for Sparse-View CT Reconstruction
by: Han, Yoseob
Published: (2025)

Attentional Graph Meta-Learning for Indoor Localization Using Extremely Sparse Fingerprints
by: Yan, Wenzhong, et al.
Published: (2025)

Unveiling Hidden Convexity in Deep Learning: a Sparse Signal Processing Perspective
by: Zeger, Emi, et al.
Published: (2026)

Koopman AutoEncoder via Singular Value Decomposition for Data-Driven Long-Term Prediction
by: Choi, Jinho, et al.
Published: (2024)

Subspace Representation Learning for Sparse Linear Arrays to Localize More Sources than Sensors: A Deep Learning Methodology
by: Chen, Kuan-Lin, et al.
Published: (2024)

Personalized Sleep Prediction via Deep Adaptive Spatiotemporal Modeling and Sparse Data
by: Wang, Xueyi, et al.
Published: (2025)

Missing Data in Signal Processing and Machine Learning: Models, Methods and Modern Approaches
by: Hippert-Ferrer, Alexandre, et al.
Published: (2025)

What Physics do Data-Driven MoCap-to-Radar Models Learn?
by: Chen, Kevin, et al.
Published: (2026)

Efficient Federated Low Rank Matrix Completion
by: Abbasi, Ahmed Ali, et al.
Published: (2024)

Efficient Matrix Factorization Via Householder Reflections
by: Dash, Anirudh, et al.
Published: (2024)

Cramer-Rao Bounds for Laplacian Matrix Estimation
by: Halihal, Morad, et al.
Published: (2025)

Bayesian Matrix Completion Under Geometric Constraints
by: Chiluvuri, Rohit Varma, et al.
Published: (2026)

Abnormality Prediction and Forecasting of Laboratory Values from Electrocardiogram Signals Using Multimodal Deep Learning
by: Alcaraz, Juan Miguel Lopez, et al.
Published: (2024)

The Transferability of Downsamped Sparse Graph Convolutional Networks
by: Shu, Qinji, et al.
Published: (2024)

Generating High Dimensional User-Specific Wireless Channels using Diffusion Models
by: Lee, Taekyun, et al.
Published: (2024)

Restoring Super-High Resolution GPS Mobility Data
by: Yonekura, Haruki, et al.
Published: (2024)