Graph Structure Learning

Follow this topic Ask about this topic

Momentum

9 papers in the last four weeks, up 50% on the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

Latest papers 95

All topics

The Regularization Parameter: Sparse Precision Matrix Estimation
Jul 7, 2026Aryan Eftekhari, Daniel Sergio Vega, Ernst-Jan Camiel Wit +1Graph Structure Learning Parameter Estimation
Institute of Computing, Faculty of Informatics, Universit`a della Svizzera italiana (USI), Lugano, Switzerland
Out-of-distribution Neural Inference in Dynamical Ising Models
Jul 3, 2026Yuan-Bin Zhu, Shuang Qiao, Shi-Ju RanGraph Structure Learning OOD Generalization
Center for Quantum Physics and Intelligent Sciences, Department of Physics, Capital Normal University, Beijing 10048, China
Transfer Learning in High-dimensional Ising Models
Jul 3, 2026Joonho Kim, Seyoung ParkGraph Structure Learning Ising Model
Kim Jaechul Graduate School of Artificial Intelligence, KAIST, Seoul, Republic of Korea · Department of Statistics and Data Science, Yonsei University, Seoul, Republic of Korea
SA-HGNN: Sample-Adaptive Hyperbolic Graph Neural Network for EEG-Based Depression Recognition
Jul 2, 2026Yang Li, Pan Hu, Yan Zhang +3Graph Structure Learning Electroencephalography
School of Software Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China
Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing
Jun 30, 2026Eric Shen, Tony Wu, Mahbod Majid +1Graph Structure Learning Probabilistic Graphical Models
MIT
Connectivity Estimation using Stochastic Graph Heat Modelling
Jun 27, 2026Stephan Goerttler, Min Wu, Fei HeGraph Structure Learning Neuroimaging
Centre for Computational Science and Mathematical Modelling, Coventry University, Coventry CV1 5FB, UK · Institute for Infocomm Research, A*STAR, Singapore
Directed Graph Topology Inference via Graph Filter Identification
Jun 25, 2026Rasoul Shafipour, Andrei Buciulea, Santiago Segarra +2Graph Signal Processing Graph Structure Learning
NVIDIA · Dept. of Signal Theory and Comms., King Juan Carlos University · Dept. of Electrical and Computer Eng., Rice University +1
Auto-Configured Explainable Graph Neural Networks for Multi-Site Pollution Prediction
Jun 23, 2026Abdelkader Dairi, Fouzi Harrou, Ying SunGraph Structure Learning Air Quality Prediction
Department of Computer Science University of Science and Technology of Oran-Mohamed Boudiaf (USTO-MB) El Mnaouar, BP 1505, Bir El Djir 31000, Oran, Algeria · Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900, Saudi Arabia
GES-TSP: Graph Edge Sparsification for TSP
Jun 23, 2026Tianfeng Chen, Xianyue LiTraveling Salesperson Problem Graph Structure Learning
School of Mathematics and Statistics Lanzhou Universtiy
Towards Federated Long-Tailed Graph Learning: An Energy-Guided Dual Decoupling Approach
Jun 23, 2026Lianshuai Guo, Zhongzheng Yuan, Xunkai Li +2Graph Structure Learning Long-Tail Learning
Shandong University, School of Airspace Science and Engineering, Weihai 264209, China · Beijing Institute of Technology, School of Computer Science and Technology, Beijing 100081, China
Low-rank Updates in Slowly Time-varying Graphs for Spatial-Temporal Signal Interpolation
Jun 22, 2026Saghar Bagheri, Gene Cheung, Tim Eadie +1Graph Signal Processing Graph Structure Learning
Department of EECS, York University, Toronto, Canada · Dept of ECE, University of Southern California, Los Angeles, CA
Bridge the Gaps: Heterogeneous Attributed Graph Clustering via Quaternion Representation Learning
Jun 22, 2026Xinxi Chen, Junyang Chen, Yiqun Zhang +2Graph Structure Learning Graph Neural Networks
School of Computer Science and Technology, Guangdong University of Technology, Guangzhou 510006, China
Learning Graphs through Continuous Information Entropy Fields
Jun 22, 2026Hui Cong, Bo Sun, Ziheng Jiao +1Graph Structure Learning Graph Neural Networks
School of Information Engineering, Chang’an University, Shaanxi, Xi’an, China · AUTHORERR: Missing \icmlaffiliation.
Ramanujan Graph Rewiring with Non Negative Resistance Curvature
Jun 19, 2026Hugo Attali, Rachid El JouhriGraph Structure Learning Graph Rewiring
Université Sorbonne Paris Nord, CNRS, LIPN, France
SLeDGe: Semi-Supervised Learning on Data Streams with Graph Structure Learning
Jun 19, 2026Heechan Moon, Kijung ShinGraph Structure Learning Graph-Based Semi-Supervised Learning
KAIST, Seoul, Republic of Korea
Recovery thresholds for hidden weighted sparse graphs
Jun 12, 2026Zhe Hou, Jingcheng LiuGraph Structure Learning Information-Theoretic Lower Bounds
State Key Laboratory for Novel Software Technology, Nanjing University
Information Lattice Learning as Probabilistic Graphical Model Structure Learning
Jun 11, 2026Haizi Yu, Lav R. VarshneyGraph Structure Learning Interpretable ML
Kocree, Inc. · AI Innovation Institute, Stony Brook University
Forecasting Is Not Attribution: Localizing Decoder Bypass in Graph-Based Neural Marketing Mix Models
Jun 10, 2026Yunbo Wang, Bolbi LiuGraph Structure Learning Feature Attribution
Department of Electrical Engineering and Computer Science University of California, Irvine · AdsGency AI
From Uniform to Learned Graph Priors: Diffusion for Structure Discovery
Jun 10, 2026Qi Shao, Hao Guo, Jiawen Chen +2Graph Structure Learning
School of Mathematics, Southeast University Nanjing, Jiangsu, China
TAROT: Task-Adaptive Refinement of LLM-prior Graphs for Few-shot Tabular Learning
Jun 10, 2026Ruxue Shi, Yili Wang, Mengnan Du +3Graph Structure Learning Few-Shot Learning
Jilin University Changchun, China · The Chinese University of Hong Kong, Shenzhen Shenzhen, China
KG-SoftMAP: Soft Knowledge-Graph Priors for Bayesian Network Structure Learning from Sparse Discrete Data
Jun 9, 2026Guoliang Xu, James E. CorterGraph Structure Learning Bayesian Networks
Columbia University
What Makes a Desired Graph for Relational Deep Learning?
Jun 7, 2026Yao Cheng, Siqiang LuoGraph Structure Learning Graph Neural Networks
Nanyang Technological University, College of Computing and Data Science, Singapore.
Vector Space of Cycles
Jun 6, 2026Moo K. Chung, Anass B. El-Yaagoubi, Hernando OmbaoGraph Structure Learning Brain Network Analysis
Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin, USA · Statistics Program, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Beyond Additivity: Causal Discovery in Location-Scale Noise Models with Hidden Variables
Jun 6, 2026Mariyam Khan, Shohei Shimizu, Thong PhamGraph Structure Learning Causal Discovery
University of Bergen · *Work conducted while a student trainee at RIKEN AIP · 2The University of Osaka +2
Graph Cascades: Contagion-Based Mesoscopic Rewiring for Structure-Aware Graph Machine Learning
Jun 3, 2026Meher Chaitanya, My Le, Luana RuizGraph Structure Learning Graph Rewiring
Johns Hopkins University Baltimore, MD 21210
Topology-Aware Gaussian Graph Repair for Robust Graph Neural Networks
Jun 2, 2026Anubha Goel, Juho KanniainenGraph Structure Learning Graph Neural Networks
Computing Science/Financial Computing and Data Analytics Group, Tampere University, Tampere, 33720, Finland
Learn When and Where to Connect: Adaptive Virtual Nodes for Dynamic Message Passing on Graphs
Jun 2, 2026Jaejun Lee, Joyce Jiyoung WhangGraph Structure Learning Graph Neural Networks
School of Computing KAIST Daejeon, Republic of Korea · Department of AI Computing KAIST Daejeon, Republic of Korea
Network Learning with Semi-relaxed Gromov-Wasserstein
Jun 1, 2026Charles Dufour, Ulysse Naepels, Leonardo V. SantoroGraph Structure Learning Latent Variable Models
EPFL, Institute of Mathematics Lausanne, Switzerland
Learning-based Directed Graph Abstraction of Combinatorial Spaces for Order-Preserving Search in Mixed-Combinatorial Nonlinear Optimization
May 31, 2026Gishnu Madhu, Feng Liu, Souma ChowdhuryGraph Structure Learning Graph Neural Networks
University at Buffalo Buffalo, New York, 14260
iLoRA: Bayesian Low-Rank Adaptation with Latent Interaction Graphs for Microbiome Diagnosis
May 28, 2026Yang Song, Yixuan Zhang, Lingfa Meng +5Graph Structure Learning Medical Diagnosis
Section of Health Data Science & AI, Department of Public Health, University of Copenhagen, Copenhagen, Denmark · University of Copenhagen, Copenhagen, Denmark · Rutgers University, New Brunswick, NJ, USA +1

Jul 7, 2026, stat.MLJ/K move · Enter open · S save

The Regularization Parameter: Sparse Precision Matrix Estimation

Aryan Eftekhari, Daniel Sergio Vega, Ernst-Jan Camiel Wit, Olaf Schenk

Institute of Computing, Faculty of Informatics, Universit`a della Svizzera italiana (USI), Lugano, Switzerland

Graph Structure Learning Parameter Estimation Sparse Recovery Hyperparameter Optimization

Open paper AskPDF arXiv

Sparse precision matrix estimation provides an interpretable and computationally efficient framework for modeling conditional dependencies in high-dimensional, low-sample-size data. A recurring challenge is appropriately selecting the regularization parameter that controls estimator sparsity and strikes a balance between underfitting and overfitting. We propose a closed-form, matrix-valued regularization parameter derived from the sampling distribution of the first-order optimality conditions of the

\ell_1

-regularized Gaussian maximum-likelihood estimator. By prescribing the probability that each nonzero entry of the estimator satisfies its optimality condition under resampling, we eliminate the need for cross-validation. The resulting regularization parameter is shown to attain asymptotic scaling properties that, under standard conditions, provide consistency and sparsistency of the estimator. On synthetic Gaussian and non-Gaussian datasets, as well as real-world gene microarray and neuroimaging applications, the proposed approach achieves estimation accuracy comparable to cross-validation, delivers superior support recovery, and reduces runtime by several orders of magnitude.

Momentum

Related topics

Latest papers 95