Throwing Vines at the Wall: Structure Learning via Random Search

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Vatter, Thibault, Nagler, Thomas
Format:	Preprint
Published:	2025
Subjects:	Methodology Machine Learning 62H05, 68T05, 62G05 G.3; I.2.6
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Leveraging Machine Learning for Official Statistics: A Statistical Manifesto
by: Puts, Marco, et al.
Published: (2024)

Augmented Functional Random Forests: Classifier Construction and Unbiased Functional Principal Components Importance through Ad-Hoc Conditional Permutations
by: Maturo, Fabrizio, et al.
Published: (2024)

When to Trust Confidence Thresholding: Calibration Diagnostics for Pseudo-Labelled Regression
by: Kurbucz, Marcell T.
Published: (2026)

Robust X-Learner: Breaking the Curse of Imbalance and Heavy Tails via Robust Cross-Imputation
by: Uehara, Eichi
Published: (2026)

Optimization-Free Topological Sort for Causal Discovery via the Schur Complement of Score Jacobians
by: Wu, Rui, et al.
Published: (2026)

A General Framework for Off-Policy Learning with Partially-Observed Reward
by: Takehi, Rikiya, et al.
Published: (2025)

Towards the Best Solution for Complex System Reliability: Can Statistics Outperform Machine Learning?
by: Gamiz, Maria Luz, et al.
Published: (2024)

When Marginals Match but Structure Fails: Covariance Fidelity in Generative Models
by: Riasat, Nazia
Published: (2026)

Spatiotemporally Consistent Multivariate Bias Correction for Climate Projections via Nested Vine Copulas
by: Meier, Theresa, et al.
Published: (2026)

SplitWise Regression: Stepwise Modeling with Adaptive Dummy Encoding
by: Kurbucz, Marcell T., et al.
Published: (2025)

Factorizable joint shift revisited
by: Tasche, Dirk
Published: (2026)

DeepCausalMMM: A Deep Learning Framework for Marketing Mix Modeling with Causal Structure Learning
by: Tirumala, Aditya Puttaparthi
Published: (2025)

The Good, the Bad, and the Ugly of Markov Boundary for Tabular Prediction
by: Wan, Shu, et al.
Published: (2026)

Iterative Exploration-Driven Sparse SDP Clustering via Thompson Sampling
by: Mun, Jongmin, et al.
Published: (2025)

ML-driven detection and reduction of ballast information in multi-modal datasets
by: Solovko, Yaroslav
Published: (2026)

Multiple data-driven missing imputation
by: Kavun, Sergii
Published: (2025)

Conservative Decisions with Risk Scores
by: Wei, Yishu, et al.
Published: (2025)

Enriched Functional Tree-Based Classifiers: A Novel Approach Leveraging Derivatives and Geometric Features
by: Maturo, Fabrizio, et al.
Published: (2024)

Deterministic Coreset Construction via Adaptive Sensitivity Trimming
by: Alpay, Faruk, et al.
Published: (2025)

Pair Correlation Factor and the Sample Complexity of Gaussian Mixtures
by: Aryan, Farzad
Published: (2025)

Batched Nonparametric Bandits via k-Nearest Neighbor UCB
by: Arya, Sakshi
Published: (2025)

Differentially Private Non Parametric Copulas: Generating synthetic data with non parametric copulas under privacy guarantees
by: Osorio-Marulanda, Pablo A., et al.
Published: (2024)

Demystifying Functional Random Forests: Novel Explainability Tools for Model Transparency in High-Dimensional Spaces
by: Maturo, Fabrizio, et al.
Published: (2024)

Machine Collaboration
by: Liu, Qingfeng, et al.
Published: (2021)

Signature-Kernel Based Evaluation Metrics for Robust Probabilistic and Tail-Event Forecasting
by: Redhead, Benjamin R., et al.
Published: (2026)

metabeta -- A fast neural model for Bayesian mixed-effects regression
by: Kipnis, Alex, et al.
Published: (2025)

Ranking of Multi-Response Experiment Treatments
by: Pebes-Trujillo, Miguel R., et al.
Published: (2024)

Optimised Support Vector Regression for California Housing Price Prediction: The Critical Role of Feature Engineering and Hyperparameter Tuning
by: Adutwum, Emmanuel
Published: (2026)

Intra-tree Column Subsampling Hinders XGBoost Learning of Ratio-like Interactions
by: Pinchuk, Mykola
Published: (2026)

Measures of Overlapping Multivariate Gaussian Clusters in Unsupervised Online Learning
by: Ožbot, Miha, et al.
Published: (2025)

Causal Parametric Drift Simulation: A Digital Twin Framework for Classifier Robustness Evaluation
by: Lafrance, Julien, et al.
Published: (2026)

Scalable Bayesian Clustering for Integrative Analysis of Multi-View Data
by: Cabral, Rafael, et al.
Published: (2024)

Jacobian-Velocity Bounds for Deployment Risk Under Covariate Drift
by: Landers, Jonathan R.
Published: (2026)

Closed-Form Beta Distribution Estimation from Sparse Statistics with Random Forest Implicit Regularization
by: Landers, Jonathan R.
Published: (2025)

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis
by: Fu, Minghao, et al.
Published: (2025)

TimeGraph: Synthetic Benchmark Datasets for Robust Time-Series Causal Discovery
by: Ferdous, Muhammad Hasan, et al.
Published: (2025)

From Point to probabilistic gradient boosting for claim frequency and severity prediction
by: Chevalier, Dominik, et al.
Published: (2024)

Quantile Additive Trend Filtering
by: Zhang, Zhi, et al.
Published: (2023)

Classifier Calibration at Scale: An Empirical Study of Model-Agnostic Post-Hoc Methods
by: Manokhin, Valery, et al.
Published: (2026)

Lightweight Defense Against Adversarial Attacks in Time Series Classification
by: Han, Yi
Published: (2025)