Image de couverture de livre

Precise Asymptotics for Spectral Methods in Mixed Generalized Linear Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhang, Yihan, Mondelli, Marco, Venkataramanan, Ramji
Format:	Preprint
Publié:	2022
Sujets:	Statistics Theory Information Theory Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Spectral Estimators for Structured Generalized Linear Models via Approximate Message Passing
par: Zhang, Yihan, et autres
Publié: (2023)

Optimal Estimation in Orthogonally Invariant Generalized Linear Models: Spectral Initialization and Approximate Message Passing
par: Zhang, Yihan, et autres
Publié: (2026)

Spectral Estimators for Multi-Index Models: Precise Asymptotics and Optimal Weak Recovery
par: Kovačević, Filip, et autres
Publié: (2025)

Mixed Regression via Approximate Message Passing
par: Tan, Nelvin, et autres
Publié: (2023)

Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods
par: Zhang, Yihan, et autres
Publié: (2024)

Inferring Change Points in Regression via Sample Weighting
par: Arpino, Gabriel, et autres
Publié: (2026)

Inferring Change Points in High-Dimensional Regression via Approximate Message Passing
par: Arpino, Gabriel, et autres
Publié: (2024)

Sharp One-Dimensional Sub-Gaussian Comparison in Convex Order
par: Zhang, Yihan
Publié: (2026)

Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models
par: Li, Gen, et autres
Publié: (2023)

Asymptotic Theory of Eigenvectors for Latent Embeddings with Generalized Laplacian Matrices
par: Fan, Jianqing, et autres
Publié: (2025)

Improved Convergence of Score-Based Diffusion Models via Prediction-Correction
par: Pedrotti, Francesco, et autres
Publié: (2023)

Shuffled Linear Regression via Spectral Matching
par: Liu, Hang, et autres
Publié: (2024)

UCB algorithms for multi-armed bandits: Precise regret and adaptive inference
par: Han, Qiyang, et autres
Publié: (2024)

Spectral Ranking Inferences based on General Multiway Comparisons
par: Fan, Jianqing, et autres
Publié: (2023)

Orthogonal Approximate Message Passing with Optimal Spectral Initializations for Rectangular Spiked Matrix Models
par: Chen, Haohua, et autres
Publié: (2025)

Thompson sampling: Precise arm-pull dynamics and adaptive inference
par: Han, Qiyang
Publié: (2026)

Max-Linear Regression by Convex Programming
par: Kim, Seonho, et autres
Publié: (2021)

High-Dimensional Asymptotics of Differentially Private PCA
par: Yun, Youngjoo, et autres
Publié: (2025)

$L^1$ Estimation: On the Optimality of Linear Estimators
par: Barnes, Leighton P., et autres
Publié: (2023)

Learning Spectral Methods by Transformers
par: He, Yihan, et autres
Publié: (2025)

Precise analysis of ridge interpolators under heavy correlations -- a Random Duality Theory view
par: Stojnic, Mihailo
Publié: (2024)

Price of Quality: Sufficient Conditions for Sparse Recovery using Mixed-Quality Data
par: Chaabouni, Youssef, et autres
Publié: (2026)

Avoiding the Price of Adaptivity: Inference in Linear Contextual Bandits via Stability
par: Praharaj, Samya, et autres
Publié: (2025)

Bayes-Optimal Estimation in Generalized Linear Models via Spatial Coupling
par: Cobo, Pablo Pascual, et autres
Publié: (2023)

Batches Stabilize the Minimum Norm Risk in High Dimensional Overparameterized Linear Regression
par: Ioushua, Shahar Stein, et autres
Publié: (2023)

The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
par: Shi, Laixi, et autres
Publié: (2023)

On the Precise Asymptotics of Universal Inference
par: Takatsu, Kenta
Publié: (2025)

Comparing Comparators in Generalization Bounds
par: Hellström, Fredrik, et autres
Publié: (2023)

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

Generalization of LiNGAM that allows confounding
par: Suzuki, Joe, et autres
Publié: (2024)

Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions
par: Zhang, Kaihong, et autres
Publié: (2024)

A Method For Bounding Tail Probabilities
par: Zlatanov, Nikola
Publié: (2024)

Order-Optimal Sequential 1-Bit Mean Estimation in General Tail Regimes
par: Lau, Ivan, et autres
Publié: (2026)

Relationship between Hölder Divergence and Functional Density Power Divergence: Intersection and Generalization
par: Kobayashi, Masahiro
Publié: (2025)

Spectral Clustering for Directed Graphs via Likelihood Estimation on Stochastic Block Models
par: Zhang, Ning, et autres
Publié: (2024)

Information limits and Thouless-Anderson-Palmer equations for spiked matrix models with structured noise
par: Barbier, Jean, et autres
Publié: (2024)

Adaptation to Intrinsic Dependence in Diffusion Language Models
par: Zhao, Yunxiao, et autres
Publié: (2026)

Minimax Hypothesis Testing for the Bradley-Terry-Luce Model
par: Makur, Anuran, et autres
Publié: (2024)

Minimax Optimality of the Probability Flow ODE for Diffusion Models
par: Cai, Changxiao, et autres
Publié: (2025)

Precise Asymptotics of Bagging Regularized M-estimators
par: Koriyama, Takuya, et autres
Publié: (2024)