On the Optimality of Misspecified Spectral Algorithms
Fuente:
arXiv
Guardado en:
| Autores principales: | Zhang, Haobo, Li, Yicheng, Lin, Qian |
|---|---|
| Formato: | Preprint |
| Publicado: |
2023
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Generalization Error Curves for Analytic Spectral Algorithms under Power-law Decay
por: Li, Yicheng, et al.
Publicado: (2024)
por: Li, Yicheng, et al.
Publicado: (2024)
Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories
por: Zhang, Haobo, et al.
Publicado: (2024)
por: Zhang, Haobo, et al.
Publicado: (2024)
Optimal Rate of Kernel Regression in Large Dimensions
por: Lu, Weihao, et al.
Publicado: (2023)
por: Lu, Weihao, et al.
Publicado: (2023)
The phase diagram of kernel interpolation in large dimensions
por: Zhang, Haobo, et al.
Publicado: (2024)
por: Zhang, Haobo, et al.
Publicado: (2024)
Alignment-Sensitive Minimax Rates for Spectral Algorithms with Learned Kernels
por: Huang, Dongming, et al.
Publicado: (2025)
por: Huang, Dongming, et al.
Publicado: (2025)
Learning Curves and Benign Overfitting of Spectral Algorithms in Large Dimensions
por: Lu, Weihao, et al.
Publicado: (2026)
por: Lu, Weihao, et al.
Publicado: (2026)
General Lower Bounds for Differentially Private Federated Learning with Arbitrary Public-Transcript Interactions
por: Li, Yicheng
Publicado: (2026)
por: Li, Yicheng
Publicado: (2026)
Optimal Confidence Band for Kernel Gradient Flow Estimator
por: Cheng, Yuqian, et al.
Publicado: (2026)
por: Cheng, Yuqian, et al.
Publicado: (2026)
On the Saturation Effects of Spectral Algorithms in Large Dimensions
por: Lu, Weihao, et al.
Publicado: (2025)
por: Lu, Weihao, et al.
Publicado: (2025)
Minimax and Adaptive Covariance Matrix Estimation under Differential Privacy
por: Cai, T. Tony, et al.
Publicado: (2026)
por: Cai, T. Tony, et al.
Publicado: (2026)
Federated PCA and Estimation for Spiked Covariance Matrices: Optimal Rates and Efficient Algorithm
por: Li, Jingyang, et al.
Publicado: (2024)
por: Li, Jingyang, et al.
Publicado: (2024)
Multimodal Bandits: Regret Lower Bounds and Optimal Algorithms
por: Réveillard, William, et al.
Publicado: (2025)
por: Réveillard, William, et al.
Publicado: (2025)
Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods
por: Zhang, Yihan, et al.
Publicado: (2024)
por: Zhang, Yihan, et al.
Publicado: (2024)
Spectral Estimators for Multi-Index Models: Precise Asymptotics and Optimal Weak Recovery
por: Kovačević, Filip, et al.
Publicado: (2025)
por: Kovačević, Filip, et al.
Publicado: (2025)
On Instability of Minimax Optimal Optimism-Based Bandit Algorithms
por: Praharaj, Samya, et al.
Publicado: (2025)
por: Praharaj, Samya, et al.
Publicado: (2025)
Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits
por: Zhou, Julien, et al.
Publicado: (2024)
por: Zhou, Julien, et al.
Publicado: (2024)
Minimax Rate-Optimal Algorithms for High-Dimensional Stochastic Linear Bandits
por: Liu, Jingyu, et al.
Publicado: (2025)
por: Liu, Jingyu, et al.
Publicado: (2025)
On the Pinsker bound of inner product kernel regression in large dimensions
por: Lu, Weihao, et al.
Publicado: (2024)
por: Lu, Weihao, et al.
Publicado: (2024)
Orthogonal Approximate Message Passing with Optimal Spectral Initializations for Rectangular Spiked Matrix Models
por: Chen, Haohua, et al.
Publicado: (2025)
por: Chen, Haohua, et al.
Publicado: (2025)
Statistical Complexity and Optimal Algorithms for Non-linear Ridge Bandits
por: Rajaraman, Nived, et al.
Publicado: (2023)
por: Rajaraman, Nived, et al.
Publicado: (2023)
Identifying All ε-Best Arms in (Misspecified) Linear Bandits
por: Li, Zhekai, et al.
Publicado: (2025)
por: Li, Zhekai, et al.
Publicado: (2025)
Optimal Estimation in Orthogonally Invariant Generalized Linear Models: Spectral Initialization and Approximate Message Passing
por: Zhang, Yihan, et al.
Publicado: (2026)
por: Zhang, Yihan, et al.
Publicado: (2026)
The Fragility of Optimized Bandit Algorithms
por: Fan, Lin, et al.
Publicado: (2021)
por: Fan, Lin, et al.
Publicado: (2021)
Adaptive variational Bayes: Optimality, computation and applications
por: Ohn, Ilsang, et al.
Publicado: (2021)
por: Ohn, Ilsang, et al.
Publicado: (2021)
Self-Distillation is Optimal Among Spectral Shrinkage Estimators in Spiked Covariance Models
por: Lecoiu, Radu, et al.
Publicado: (2026)
por: Lecoiu, Radu, et al.
Publicado: (2026)
Minimax-Optimal Spectral Clustering with Covariance Projection for High-Dimensional Anisotropic Mixtures
por: Huang, Chengzhu, et al.
Publicado: (2025)
por: Huang, Chengzhu, et al.
Publicado: (2025)
Differentially Private Sliced Inverse Regression: Minimax Optimality and Algorithm
por: Xia, Xintao, et al.
Publicado: (2024)
por: Xia, Xintao, et al.
Publicado: (2024)
On Spectral Learning for Odeco Tensors: Perturbation, Initialization, and Algorithms
por: Auddy, Arnab, et al.
Publicado: (2025)
por: Auddy, Arnab, et al.
Publicado: (2025)
Contextual Dynamic Pricing: Algorithms, Optimality, and Local Differential Privacy Constraints
por: Zhao, Zifeng, et al.
Publicado: (2024)
por: Zhao, Zifeng, et al.
Publicado: (2024)
Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral Methods and Graph Convolutional Networks
por: Wang, Hai-Xiao, et al.
Publicado: (2024)
por: Wang, Hai-Xiao, et al.
Publicado: (2024)
Spectrally-Corrected and Regularized QDA Classifier for Spiked Covariance Model
por: Luo, Wenya, et al.
Publicado: (2025)
por: Luo, Wenya, et al.
Publicado: (2025)
Learning Spectral Methods by Transformers
por: He, Yihan, et al.
Publicado: (2025)
por: He, Yihan, et al.
Publicado: (2025)
Optimal Convergence Analysis of DDPM for General Distributions
por: Jiao, Yuchen, et al.
Publicado: (2025)
por: Jiao, Yuchen, et al.
Publicado: (2025)
Precise Asymptotics for Spectral Methods in Mixed Generalized Linear Models
por: Zhang, Yihan, et al.
Publicado: (2022)
por: Zhang, Yihan, et al.
Publicado: (2022)
Adjacency Spectral Embeddings of Correlation Networks
por: Levin, Keith
Publicado: (2026)
por: Levin, Keith
Publicado: (2026)
Optimality of Approximate Message Passing Algorithms for Spiked Matrix Models with Rotationally Invariant Noise
por: Dudeja, Rishabh, et al.
Publicado: (2024)
por: Dudeja, Rishabh, et al.
Publicado: (2024)
Leave-one-out Singular Subspace Perturbation Analysis for Spectral Clustering
por: Zhang, Anderson Y., et al.
Publicado: (2022)
por: Zhang, Anderson Y., et al.
Publicado: (2022)
Minimax Optimality of the Probability Flow ODE for Diffusion Models
por: Cai, Changxiao, et al.
Publicado: (2025)
por: Cai, Changxiao, et al.
Publicado: (2025)
Enjoying Non-linearity in Multinomial Logistic Bandits: A Minimax-Optimal Algorithm
por: Boudart, Pierre, et al.
Publicado: (2025)
por: Boudart, Pierre, et al.
Publicado: (2025)
Entrywise Error Bounds for Spectral Ranking with Semi-Random Adversaries
por: Lee, Dongmin, et al.
Publicado: (2026)
por: Lee, Dongmin, et al.
Publicado: (2026)
Ejemplares similares
-
Generalization Error Curves for Analytic Spectral Algorithms under Power-law Decay
por: Li, Yicheng, et al.
Publicado: (2024) -
Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories
por: Zhang, Haobo, et al.
Publicado: (2024) -
Optimal Rate of Kernel Regression in Large Dimensions
por: Lu, Weihao, et al.
Publicado: (2023) -
The phase diagram of kernel interpolation in large dimensions
por: Zhang, Haobo, et al.
Publicado: (2024) -
Alignment-Sensitive Minimax Rates for Spectral Algorithms with Learned Kernels
por: Huang, Dongming, et al.
Publicado: (2025)