Spectral gap of Metropolis-within-Gibbs under log-concavity
Fuente:
arXiv
Saved in:
| Main Authors: | Secchi, Cecilia, Zanella, Giacomo |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Entropy contraction of the Gibbs sampler under log-concavity
by: Ascolani, Filippo, et al.
Published: (2024)
by: Ascolani, Filippo, et al.
Published: (2024)
Scalability of Metropolis-within-Gibbs schemes for high-dimensional Bayesian models
by: Ascolani, Filippo, et al.
Published: (2024)
by: Ascolani, Filippo, et al.
Published: (2024)
Convergence rate of random scan Coordinate Ascent Variational Inference under log-concavity
by: Lavenant, Hugo, et al.
Published: (2024)
by: Lavenant, Hugo, et al.
Published: (2024)
Conjugate gradient methods for high-dimensional GLMMs
by: Pandolfi, Andrea, et al.
Published: (2024)
by: Pandolfi, Andrea, et al.
Published: (2024)
Universal Inference Meets Random Projections: A Scalable Test for Log-concavity
by: Dunn, Robin, et al.
Published: (2021)
by: Dunn, Robin, et al.
Published: (2021)
Strong log-concavity in probit regression
by: Chak, Martin, et al.
Published: (2026)
by: Chak, Martin, et al.
Published: (2026)
A mixing time bound for Gibbs sampling from log-smooth log-concave distributions
by: Wadia, Neha S.
Published: (2024)
by: Wadia, Neha S.
Published: (2024)
Structural Effect and Spectral Enhancement of High-Dimensional Regularized Linear Discriminant Analysis
by: Zhang, Yonghan, et al.
Published: (2025)
by: Zhang, Yonghan, et al.
Published: (2025)
Minimax-Optimal Spectral Clustering with Covariance Projection for High-Dimensional Anisotropic Mixtures
by: Huang, Chengzhu, et al.
Published: (2025)
by: Huang, Chengzhu, et al.
Published: (2025)
Self-Distillation is Optimal Among Spectral Shrinkage Estimators in Spiked Covariance Models
by: Lecoiu, Radu, et al.
Published: (2026)
by: Lecoiu, Radu, et al.
Published: (2026)
On the fundamental limitations of multiproposal Markov chain Monte Carlo algorithms
by: Pozza, Francesco, et al.
Published: (2024)
by: Pozza, Francesco, et al.
Published: (2024)
Zeroth-order parallel sampling
by: Pozza, Francesco, et al.
Published: (2026)
by: Pozza, Francesco, et al.
Published: (2026)
Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression
by: Ascolani, Filippo, et al.
Published: (2025)
by: Ascolani, Filippo, et al.
Published: (2025)
Neural Conditional Probability for Uncertainty Quantification
by: Kostic, Vladimir R., et al.
Published: (2024)
by: Kostic, Vladimir R., et al.
Published: (2024)
Spectral Ranking Inferences based on General Multiway Comparisons
by: Fan, Jianqing, et al.
Published: (2023)
by: Fan, Jianqing, et al.
Published: (2023)
Statistical Inference under Adaptive Sampling with LinUCB
by: Fan, Wei, et al.
Published: (2025)
by: Fan, Wei, et al.
Published: (2025)
Rescuing double robustness: safe estimation under complete misspecification
by: Testa, Lorenzo, et al.
Published: (2025)
by: Testa, Lorenzo, et al.
Published: (2025)
Learning under Latent Group Sparsity via Diffusion on Networks
by: Ghosh, Subhroshekhar, et al.
Published: (2025)
by: Ghosh, Subhroshekhar, et al.
Published: (2025)
Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift
by: Ge, Jiawei, et al.
Published: (2024)
by: Ge, Jiawei, et al.
Published: (2024)
Discovering Causal Relationships using Proxy Variables under Unmeasured Confounding
by: Wu, Yong, et al.
Published: (2025)
by: Wu, Yong, et al.
Published: (2025)
Asymptotic Behavior of Adversarial Training Estimator under $\ell_\infty$-Perturbation
by: Xie, Yiling, et al.
Published: (2024)
by: Xie, Yiling, et al.
Published: (2024)
Efficient and Multiply Robust Risk Estimation under General Forms of Dataset Shift
by: Qiu, Hongxiang, et al.
Published: (2023)
by: Qiu, Hongxiang, et al.
Published: (2023)
Conformal Prediction under Levy-Prokhorov Distribution Shifts: Robustness to Local and Global Perturbations
by: Aolaritei, Liviu, et al.
Published: (2025)
by: Aolaritei, Liviu, et al.
Published: (2025)
Optimal Nuisance Function Tuning for Estimating a Doubly Robust Functional under Proportional Asymptotics
by: McGrath, Sean, et al.
Published: (2025)
by: McGrath, Sean, et al.
Published: (2025)
Transfer Learning for Classification under Decision Rule Drift with Application to Optimal Individualized Treatment Rule Estimation
by: Wang, Xiaohan, et al.
Published: (2025)
by: Wang, Xiaohan, et al.
Published: (2025)
Double Robust Semi-Supervised Inference for the Mean: Selection Bias under MAR Labeling with Decaying Overlap
by: Zhang, Yuqian, et al.
Published: (2021)
by: Zhang, Yuqian, et al.
Published: (2021)
Non-asymptotic error bounds for probability flow ODEs under weak log-concavity
by: Kremling, Gitte, et al.
Published: (2025)
by: Kremling, Gitte, et al.
Published: (2025)
A Double Machine Learning Approach for the Evaluation of COVID-19 Vaccine Effectiveness under the Test-Negative Design: Analysis of Québec Administrative Data
by: Jiang, Cong, et al.
Published: (2023)
by: Jiang, Cong, et al.
Published: (2023)
Functional Data Representation with Merge Trees
by: Pegoraro, Matteo, et al.
Published: (2021)
by: Pegoraro, Matteo, et al.
Published: (2021)
High-dimensional Clustering and Signal Recovery under Block Signals
by: Su, Wu, et al.
Published: (2025)
by: Su, Wu, et al.
Published: (2025)
The Local Approach to Causal Inference under Network Interference
by: Auerbach, Eric, et al.
Published: (2021)
by: Auerbach, Eric, et al.
Published: (2021)
Dynamic treatment effects: high-dimensional inference under model misspecification
by: Zhang, Yuqian, et al.
Published: (2021)
by: Zhang, Yuqian, et al.
Published: (2021)
High-accuracy sampling for diffusion models and log-concave distributions
by: Chen, Fan, et al.
Published: (2026)
by: Chen, Fan, et al.
Published: (2026)
Method-of-Moments Inference for GLMs and Doubly Robust Functionals under Proportional Asymptotics
by: Chen, Xingyu, et al.
Published: (2024)
by: Chen, Xingyu, et al.
Published: (2024)
A Unified Framework for Debiased Machine Learning: Riesz Representer Fitting under Bregman Divergence
by: Kato, Masahiro
Published: (2026)
by: Kato, Masahiro
Published: (2026)
Beyond the Average: Distributional Causal Inference under Imperfect Compliance
by: Byambadalai, Undral, et al.
Published: (2025)
by: Byambadalai, Undral, et al.
Published: (2025)
Log-concave Density Estimation with Independent Components
by: Kubal, Sharvaj, et al.
Published: (2024)
by: Kubal, Sharvaj, et al.
Published: (2024)
Distributional Treatment Effect Estimation across Heterogeneous Sites via Optimal Transport
by: Bateni, Borna, et al.
Published: (2025)
by: Bateni, Borna, et al.
Published: (2025)
Strongly Consistent Community Detection in Popularity Adjusted Block Models
by: Yuan, Quan, et al.
Published: (2025)
by: Yuan, Quan, et al.
Published: (2025)
The BdryMatérn GP: Reliable incorporation of boundary information on irregular domains for Gaussian process modeling
by: Ding, Liang, et al.
Published: (2025)
by: Ding, Liang, et al.
Published: (2025)
Similar Items
-
Entropy contraction of the Gibbs sampler under log-concavity
by: Ascolani, Filippo, et al.
Published: (2024) -
Scalability of Metropolis-within-Gibbs schemes for high-dimensional Bayesian models
by: Ascolani, Filippo, et al.
Published: (2024) -
Convergence rate of random scan Coordinate Ascent Variational Inference under log-concavity
by: Lavenant, Hugo, et al.
Published: (2024) -
Conjugate gradient methods for high-dimensional GLMMs
by: Pandolfi, Andrea, et al.
Published: (2024) -
Universal Inference Meets Random Projections: A Scalable Test for Log-concavity
by: Dunn, Robin, et al.
Published: (2021)