Cover Image

Sparse Mixture Models inspired by ANOVA Decompositions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hertrich, Johannes, Ba, Fatima Antarou, Steidl, Gabriele
Format:	Preprint
Published:	2021
Subjects:	Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Sparse additive function decompositions facing basis transforms
by: Ba, Fatima Antarou, et al.
Published: (2024)

Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems
by: Altekrüger, Fabian, et al.
Published: (2023)

Mixed Noise and Posterior Estimation with Conditional DeepGEM
by: Hagemann, Paul, et al.
Published: (2024)

ANOVA for High-dimensional Non-stationary Time Series
by: Zhang, Yunyi
Published: (2025)

Tensor Product Neural Networks for Functional ANOVA Model
by: Park, Seokhun, et al.
Published: (2025)

Bayesian Sparse Gaussian Mixture Model in High Dimensions
by: Yao, Dapeng, et al.
Published: (2022)

Efficient estimation with incomplete data via generalised ANOVA decompositions
by: Berrett, Thomas B.
Published: (2024)

META-ANOVA: Screening interactions for interpretable machine learning
by: Choi, Yongchan, et al.
Published: (2024)

Sparse Factor Analysis for Categorical Data with the Group-Sparse Generalized Singular Value Decomposition
by: Yu, Ju-Chi, et al.
Published: (2024)

Testing Against Tree Ordered Alternatives in One-way ANOVA
by: Halder, Subha, et al.
Published: (2025)

Effect-Wise Inference for Smoothing Spline ANOVA on Tensor-Product Sobolev Space
by: Cho, Youngjin, et al.
Published: (2026)

Functional ANOVA approaches for detecting changes in air pollution during the COVID-19 pandemic
by: Acal, Christian, et al.
Published: (2024)

Shift-Dispersion Decompositions of Wasserstein and Cramér Distances
by: Resin, Johannes, et al.
Published: (2024)

Convolutional Proximal Neural Networks and Plug-and-Play Algorithms
by: Hertrich, Johannes, et al.
Published: (2020)

Neural Wasserstein Gradient Flows for Maximum Mean Discrepancies with Riesz Kernels
by: Altekrüger, Fabian, et al.
Published: (2023)

Provably Efficient Posterior Sampling for Sparse Linear Regression via Measure Decomposition
by: Montanari, Andrea, et al.
Published: (2024)

Estimation and Hypothesis Testing of Derivatives in Smoothing Spline ANOVA Models
by: Liu, Ruiqi, et al.
Published: (2023)

Heavy-Tailed NGG Mixture Models
by: Ramirez, Vianey Palacios, et al.
Published: (2022)

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

Restricted Spectral Gap Decomposition for Simulated Tempering Targeting Mixture Distributions
by: Garg, Jhanvi, et al.
Published: (2025)

Mixture Matrix-valued Autoregressive Model
by: Wu, Fei, et al.
Published: (2023)

Optimal Sparse Singular Value Decomposition for High-dimensional High-order Data
by: Zhang, Anru, et al.
Published: (2018)

Structurally Aware Robust Model Selection for Mixtures
by: Li, Jiawei, et al.
Published: (2024)

Projective, Sparse, and Learnable Latent Position Network Models
by: Spencer, Neil A., et al.
Published: (2017)

Convergence and Optimality of the EM Algorithm Under Multi-Component Gaussian Mixture Models
by: Bing, Xin, et al.
Published: (2025)

On the Entropy of General Mixture Distributions
by: Lee, Namyoon
Published: (2026)

The Canonical Decomposition of Factor Models: Weak Factors are Everywhere
by: Gersing, Philipp, et al.
Published: (2023)

Information-Geometric Decomposition of Generalization Error in Unsupervised Learning
by: Kim, Gilhan
Published: (2026)

Sliced Space-filling Design with Mixtures
by: Xiong, Zikang, et al.
Published: (2025)

Modeling Extreme Events in the Presence of Inlier: A Mixture Approach
by: Nila, Shivshankar, et al.
Published: (2025)

Local Minima Structures in Gaussian Mixture Models
by: Chen, Yudong, et al.
Published: (2020)

The Bernstein-von Mises theorem for Semiparametric Mixtures
by: Franssen, Stefan, et al.
Published: (2024)

Robust Sparse Recovery with Sparse Bernoulli matrices via Expanders
by: Abdalla, Pedro
Published: (2021)

Online Sparse Regression with Expanding Observables
by: Yang, Ying, et al.
Published: (2026)

Mixtures of Discrete Decomposable Graphical Models
by: Alexandr, Yulia, et al.
Published: (2024)

A renormalization-group inspired lattice-based framework for piecewise generalized linear models
by: Chang, Joshua C.
Published: (2026)

Wasserstein Gradient Flows of the Discrepancy with Distance Kernel on the Line
by: Hertrich, Johannes, et al.
Published: (2023)

Wasserstein Steepest Descent Flows of Discrepancies with Riesz Kernels
by: Hertrich, Johannes, et al.
Published: (2022)

Matching Criterion for Identifiability in Sparse Factor Analysis
by: Sturma, Nils, et al.
Published: (2025)

Strong Consistency of Sparse K-means Clustering
by: Kim, Jeungju, et al.
Published: (2025)