{"total":58,"rows":[{"id":"2205.13709","title":"DP-PCA: Statistically Optimal and Differentially Private PCA","created":"2022-05-27","cited_by_count":24,"area":null},{"id":"2102.03646","title":"Streaming k-PCA: Efficient guarantees for Oja's algorithm, beyond rank-one updates","created":"2021-02-06","cited_by_count":21,"area":null},{"id":"2102.03990","title":"DeEPCA: Decentralized Exact PCA with Linear Convergence Rate","created":"2021-02-08","cited_by_count":18,"area":null},{"id":"2106.00001","title":"Privately Learning Subspaces","created":"2021-05-28","cited_by_count":16,"area":null},{"id":"2107.04518","title":"Optimal Gradient-based Algorithms for Non-concave Bandit Optimization","created":"2021-07-09","cited_by_count":15,"area":null},{"id":"2309.05505","title":"Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning","created":"2023-09-11","cited_by_count":13,"area":null},{"id":"2104.00512","title":"On the Optimality of the Oja's Algorithm for Online PCA","created":"2021-03-31","cited_by_count":11,"area":null},{"id":"2106.14857","title":"Bootstrapping the error of Oja's algorithm","created":"2021-06-28","cited_by_count":11,"area":null},{"id":"2107.09802","title":"Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates","created":"2021-07-20","cited_by_count":10,"area":null},{"id":"2402.11156","title":"Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits","created":"2024-02-17","cited_by_count":10,"area":null},{"id":"2102.08341","title":"Faster Kernel Matrix Algebra via Density Estimation","created":"2021-02-16","cited_by_count":8,"area":null},{"id":"2207.11208","title":"Statistical and Computational Trade-offs in Variational Inference: A Case Study in Inferential Model Selection","created":"2022-07-22","cited_by_count":7,"area":null},{"id":"2403.03905","title":"Black-Box $k$-to-$1$-PCA Reductions: Theory and Applications","created":"2024-03-06","cited_by_count":7,"area":null},{"id":"2306.08745","title":"PLAN: Variance-Aware Private Mean Estimation","created":"2023-06-14","cited_by_count":6,"area":null},{"id":"2411.01931","title":"Differentially private and decentralized randomized power method","created":"2024-11-04","cited_by_count":6,"area":null},{"id":"2110.13265","title":"On the Second-order Convergence Properties of Random Search Methods","created":"2021-10-25","cited_by_count":5,"area":null},{"id":"2202.06442","title":"Fast algorithm for overcomplete order-3 tensor decomposition","created":"2022-02-14","cited_by_count":5,"area":null},{"id":"2303.04555","title":"Streaming Kernel PCA Algorithm With Small Space","created":"2023-03-08","cited_by_count":5,"area":null},{"id":"2310.18593","title":"Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint","created":"2023-10-28","cited_by_count":5,"area":null},{"id":"2103.00704","title":"FedPower: Privacy-Preserving Distributed Eigenspace Estimation","created":"2021-03-01","cited_by_count":4,"area":null},{"id":"2203.09276","title":"Stochastic and Private Nonconvex Outlier-Robust PCA","created":"2022-03-17","cited_by_count":4,"area":null},{"id":"2305.17148","title":"Differentially Private Low-dimensional Synthetic Data from High-dimensional Datasets","created":"2023-05-26","cited_by_count":4,"area":null},{"id":"2508.10879","title":"An Iterative Algorithm for Differentially Private $k$-PCA with Adaptive Noise","created":"2025-08-14","cited_by_count":3,"area":null},{"id":"2510.22440","title":"Low-Precision Streaming PCA","created":"2025-10-25","cited_by_count":3,"area":null},{"id":"2510.25670","title":"Spectral Perturbation Bounds for Low-Rank Approximation with Applications to Privacy","created":"2025-10-29","cited_by_count":3,"area":null},{"id":"2205.12109","title":"Federated singular value decomposition for high dimensional data","created":"2022-05-24","cited_by_count":2,"area":null},{"id":"2303.08902","title":"Learning ground states of gapped quantum Hamiltonians with Kernel Methods","created":"2023-03-15","cited_by_count":2,"area":null},{"id":"2408.10332","title":"Spectral Guarantees for Adversarial Streaming PCA","created":"2024-08-19","cited_by_count":2,"area":null},{"id":"2409.08771","title":"In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting","created":"2024-09-13","cited_by_count":2,"area":null},{"id":"2505.05816","title":"On the Price of Differential Privacy for Spectral Clustering over Stochastic Block Models","created":"2025-05-09","cited_by_count":2,"area":null},{"id":"2108.09264","title":"Practical and Fast Momentum-Based Power Methods","created":"2021-08-20","cited_by_count":1,"area":null},{"id":"2202.04719","title":"Multivariate Analysis for Multiple Network Data via Semi-Symmetric Tensor PCA","created":"2022-02-09","cited_by_count":1,"area":null},{"id":"2402.06465","title":"On Differentially Private Subspace Estimation in a Distribution-Free Setting","created":"2024-02-09","cited_by_count":1,"area":null},{"id":"2412.00497","title":"Distributed Differentially Private Data Analytics via Secure Sketching","created":"2024-11-30","cited_by_count":1,"area":null},{"id":"2507.22849","title":"Decentralized Differentially Private Power Method","created":"2025-07-30","cited_by_count":1,"area":null},{"id":"2511.01303","title":"Differentially Private Nonparametric Confidence Intervals Under Minimal Distributional Assumptions","created":"2025-11-03","cited_by_count":1,"area":null},{"id":"2602.11454","title":"Adaptive Power Iteration Method for Differentially Private PCA","created":"2026-02-12","cited_by_count":1,"area":null},{"id":"2605.28684","title":"History-aware adaptive reduced-order models via incremental singular value decomposition","created":"2026-05-27","cited_by_count":1,"area":null},{"id":"2606.21951","title":"On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA","created":"2026-06-20","cited_by_count":1,"area":null},{"id":"2609.26508","title":"Gap-Free Streaming PCA Beyond Rank-One Updates: Near-Optimal Rates and Applications to Differential Privacy","created":"2026-09-22","cited_by_count":1,"area":null},{"id":"2110.03273","title":"AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow","created":"2021-10-07","cited_by_count":0,"area":null},{"id":"2202.07992","title":"Improved analysis of randomized SVD for top-eigenvector approximation","created":"2022-02-16","cited_by_count":0,"area":null},{"id":"2304.09096","title":"Privacy-Preserving Matrix Factorization for Recommendation Systems using Gaussian Mechanism","created":"2023-04-11","cited_by_count":0,"area":null},{"id":"2309.14512","title":"Byzantine-Resilient Federated PCA and Low Rank Column-wise Sensing","created":"2023-09-25","cited_by_count":0,"area":null},{"id":"2405.06569","title":"Efficient Federated Low Rank Matrix Completion","created":"2024-05-10","cited_by_count":0,"area":null},{"id":"2408.17151","title":"Investigating Privacy Leakage in Dimensionality Reduction Methods via Reconstruction Attack","created":"2024-08-30","cited_by_count":0,"area":null},{"id":"2502.00320","title":"$k$-SVD with Gradient Descent","created":"2025-02-01","cited_by_count":0,"area":null},{"id":"2503.13644","title":"Quantum EigenGame for excited state calculation","created":"2025-03-17","cited_by_count":0,"area":null},{"id":"2504.14741","title":"AltGDmin: Alternating GD and Minimization for Partly-Decoupled (Federated) Optimization","created":"2025-04-20","cited_by_count":0,"area":null},{"id":"2505.03858","title":"Differentially Private and Scalable Estimation of the Network Principal Component","created":"2025-05-06","cited_by_count":0,"area":null},{"id":"2510.07136","title":"Differentially Private Spectral Graph Clustering: Balancing Privacy, Accuracy, and Efficiency","created":"2025-10-08","cited_by_count":0,"area":null},{"id":"2512.22675","title":"Beyond Centralization: Provable Communication Efficient Decentralized Multi-Task Learning","created":"2025-12-27","cited_by_count":0,"area":null},{"id":"2602.03682","title":"Improved Analysis of the Accelerated Noisy Power Method with Applications to Decentralized PCA","created":"2026-02-03","cited_by_count":0,"area":null},{"id":"2605.09755","title":"Accelerating Power Method with Fast Sketching for Stronger Low-Rank Approximation","created":"2026-05-10","cited_by_count":0,"area":null},{"id":"2606.21107","title":"Enhancing Differentially Private Mechanisms via Empirical Bayes","created":"2026-06-19","cited_by_count":0,"area":null},{"id":"2606.24938","title":"Privacy-preserving federated tensor decomposition of single-cell immune data: recovering multicellular programs across institutions","created":"2026-06-22","cited_by_count":0,"area":null},{"id":"2608.04406","title":"Incremental Aggregation on the Grassmannian for Asynchronous Eigenspace Computation","created":"2026-08-05","cited_by_count":0,"area":null},{"id":"2609.31614","title":"Gap-free Differentially Private PCA for Gaussian Data","created":"2026-09-25","cited_by_count":0,"area":null}],"next_cursor":null}