Cover Image

Federated PCA and Estimation for Spiked Covariance Matrices: Optimal Rates and Efficient Algorithm

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Jingyang, Cai, T. Tony, Xia, Dong, Zhang, Anru R.
Format:	Preprint
Published:	2024
Subjects:	Statistics Theory Information Theory Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Optimal Differentially Private PCA and Estimation for Spiked Covariance Matrices
by: Cai, T. Tony, et al.
Published: (2024)

Mode-wise Principal Subspace Pursuit and Matrix Spiked Covariance Model
by: Tang, Runshi, et al.
Published: (2023)

Minimax and Adaptive Covariance Matrix Estimation under Differential Privacy
by: Cai, T. Tony, et al.
Published: (2026)

Optimality of Approximate Message Passing Algorithms for Spiked Matrix Models with Rotationally Invariant Noise
by: Dudeja, Rishabh, et al.
Published: (2024)

Robust Estimation Under Heterogeneous Corruption Rates
by: Chaudhuri, Syomantak, et al.
Published: (2025)

Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCA
by: Zhou, Yuchen, et al.
Published: (2023)

An Iterative Algorithm for Differentially Private $k$-PCA with Adaptive Noise
by: Düngler, Johanna, et al.
Published: (2025)

Orthogonal Approximate Message Passing with Optimal Spectral Initializations for Rectangular Spiked Matrix Models
by: Chen, Haohua, et al.
Published: (2025)

Minimax Optimality of the Probability Flow ODE for Diffusion Models
by: Cai, Changxiao, et al.
Published: (2025)

$L^1$ Estimation: On the Optimality of Linear Estimators
by: Barnes, Leighton P., et al.
Published: (2023)

Orthogonal Approximate Message Passing Algorithms for Rectangular Spiked Matrix Models with Rotationally Invariant Noise
by: Chen, Haohua, et al.
Published: (2026)

Inference for Heteroskedastic PCA with Missing Data
by: Yan, Yuling, et al.
Published: (2021)

High-Dimensional Asymptotics of Differentially Private PCA
by: Yun, Youngjoo, et al.
Published: (2025)

On Instability of Minimax Optimal Optimism-Based Bandit Algorithms
by: Praharaj, Samya, et al.
Published: (2025)

Statistical-Computational Trade-offs in Tensor PCA and Related Problems via Communication Complexity
by: Dudeja, Rishabh, et al.
Published: (2022)

Statistical Complexity and Optimal Algorithms for Non-linear Ridge Bandits
by: Rajaraman, Nived, et al.
Published: (2023)

Self-Distillation is Optimal Among Spectral Shrinkage Estimators in Spiked Covariance Models
by: Lecoiu, Radu, et al.
Published: (2026)

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

Diffusion Models Are Statistically Optimal for Learning Low-Dimensional Multi-Modal Distributions
by: Wu, Jingda, et al.
Published: (2026)

Instance-Optimal Estimation with Multiple LLM Judges on a Budget
by: Lee, Junghyun, et al.
Published: (2026)

Sequential 1-bit Mean Estimation with Near-Optimal Sample Complexity
by: Lau, Ivan, et al.
Published: (2025)

Asymptotic Theory of Eigenvectors for Latent Embeddings with Generalized Laplacian Matrices
by: Fan, Jianqing, et al.
Published: (2025)

Order-Optimal Sequential 1-Bit Mean Estimation in General Tail Regimes
by: Lau, Ivan, et al.
Published: (2026)

Constrained Gaussian Wasserstein Optimal Transport with Commutative Covariance Matrices
by: Chen, Jun, et al.
Published: (2025)

Spectral Estimators for Multi-Index Models: Precise Asymptotics and Optimal Weak Recovery
by: Kovačević, Filip, et al.
Published: (2025)

Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits
by: Zhou, Julien, et al.
Published: (2024)

CoinPress: Practical Private Mean and Covariance Estimation
by: Biswas, Sourav, et al.
Published: (2020)

MESSY Estimation: Maximum-Entropy based Stochastic and Symbolic densitY Estimation
by: Tohme, Tony, et al.
Published: (2023)

Optimal Estimation in Orthogonally Invariant Generalized Linear Models: Spectral Initialization and Approximate Message Passing
by: Zhang, Yihan, et al.
Published: (2026)

Just Wing It: Near-Optimal Estimation of Missing Mass in a Markovian Sequence
by: Pananjady, Ashwin, et al.
Published: (2024)

Breaking AR's Sampling Bottleneck: Provable Acceleration via Diffusion Language Models
by: Li, Gen, et al.
Published: (2025)

Generalization for Least Squares Regression With Simple Spiked Covariances
by: Li, Jiping, et al.
Published: (2024)

Online Covariance Estimation in Averaged SGD: Improved Batch-Mean Rates and Minimax Optimality via Trajectory Regression
by: Ni, Yijin, et al.
Published: (2026)

Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions
by: Zhang, Kaihong, et al.
Published: (2024)

Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
by: Li, Gen, et al.
Published: (2021)

Optimal Anytime-Valid Tests for Composite Nulls
by: Shekhar, Shubhanshu
Published: (2025)

Oja's Algorithm for Streaming Sparse PCA
by: Kumar, Syamantak, et al.
Published: (2024)

Spectrally-Corrected and Regularized QDA Classifier for Spiked Covariance Model
by: Luo, Wenya, et al.
Published: (2025)

Optimal training-conditional regret for online conformal prediction
by: Liang, Jiadong, et al.
Published: (2026)

Estimating Higher-Order Mixed Memberships via the $\ell_{2,\infty}$ Tensor Perturbation Bound
by: Agterberg, Joshua, et al.
Published: (2022)