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Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with
  Minimax Optimal Rates
v1v2 (latest)

Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates

22 May 2013
Yuchen Zhang
John C. Duchi
Martin J. Wainwright
ArXiv (abs)PDFHTML

Papers citing "Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates"

50 / 148 papers shown
Title
Learning Theory of Decentralized Robust Kernel-Based Learning Algorithm
Zhan Yu
149
0
0
05 Jun 2025
Free Random Projection for In-Context Reinforcement Learning
Free Random Projection for In-Context Reinforcement Learning
Tomohiro Hayase
B. Collins
Nakamasa Inoue
91
0
0
09 Apr 2025
Supervised Kernel Thinning
Supervised Kernel Thinning
Albert Gong
Kyuseong Choi
Raaz Dwivedi
177
0
0
17 Oct 2024
Distributed Learning with Discretely Observed Functional Data
Distributed Learning with Discretely Observed Functional Data
Jiading Liu
Lei Shi
48
0
0
03 Oct 2024
Optimal Kernel Quantile Learning with Random Features
Optimal Kernel Quantile Learning with Random Features
Caixing Wang
Xingdong Feng
148
1
0
24 Aug 2024
Byzantine-tolerant distributed learning of finite mixture models
Byzantine-tolerant distributed learning of finite mixture models
Qiong Zhang
Jiahua Chen
Jiahua Chen
FedML
144
0
0
19 Jul 2024
ROTI-GCV: Generalized Cross-Validation for right-ROTationally Invariant
  Data
ROTI-GCV: Generalized Cross-Validation for right-ROTationally Invariant Data
Kevin Luo
Yufan Li
Pragya Sur
89
3
0
17 Jun 2024
Accelerating Heterogeneous Federated Learning with Closed-form
  Classifiers
Accelerating Heterogeneous Federated Learning with Closed-form Classifiers
Eros Fani
Raffaello Camoriano
Barbara Caputo
Marco Ciccone
86
4
0
03 Jun 2024
Decentralized Kernel Ridge Regression Based on Data-Dependent Random
  Feature
Decentralized Kernel Ridge Regression Based on Data-Dependent Random Feature
Ruikai Yang
Fan He
Mingzhen He
Jie Yang
Xiaolin Huang
143
2
0
13 May 2024
Distributed High-Dimensional Quantile Regression: Estimation Efficiency
  and Support Recovery
Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery
Caixing Wang
Ziliang Shen
71
0
0
13 May 2024
Adaptive Parameter Selection for Kernel Ridge Regression
Adaptive Parameter Selection for Kernel Ridge Regression
Shao-Bo Lin
26
3
0
10 Dec 2023
Federated Online and Bandit Convex Optimization
Federated Online and Bandit Convex Optimization
Kumar Kshitij Patel
Lingxiao Wang
Aadirupa Saha
Nathan Srebro
FedML
79
9
0
29 Nov 2023
Distributed Uncertainty Quantification of Kernel Interpolation on
  Spheres
Distributed Uncertainty Quantification of Kernel Interpolation on Spheres
Shao-Bo Lin
Xingping Sun
Di Wang
18
3
0
25 Oct 2023
Adaptive Distributed Kernel Ridge Regression: A Feasible Distributed
  Learning Scheme for Data Silos
Adaptive Distributed Kernel Ridge Regression: A Feasible Distributed Learning Scheme for Data Silos
Di Wang
Xiaotong Liu
Shao-Bo Lin
Ding-Xuan Zhou
75
0
0
08 Sep 2023
Estimation and Hypothesis Testing of Derivatives in Smoothing Spline
  ANOVA Models
Estimation and Hypothesis Testing of Derivatives in Smoothing Spline ANOVA Models
Ruiqi Liu
Kexuan Li
Meng Li
15
3
0
26 Aug 2023
Locally Adaptive and Differentiable Regression
Locally Adaptive and Differentiable Regression
Mingxuan Han
Varun Shankar
J. M. Phillips
Chenglong Ye
94
2
0
14 Aug 2023
Nonlinear Meta-Learning Can Guarantee Faster Rates
Nonlinear Meta-Learning Can Guarantee Faster Rates
Dimitri Meunier
Zhu Li
Arthur Gretton
Samory Kpotufe
176
7
0
20 Jul 2023
Estimation of an Order Book Dependent Hawkes Process for Large Datasets
Estimation of an Order Book Dependent Hawkes Process for Large Datasets
Luca Mucciante
Alessio Sancetta
25
4
0
18 Jul 2023
Intuitionistic Fuzzy Broad Learning System: Enhancing Robustness Against
  Noise and Outliers
Intuitionistic Fuzzy Broad Learning System: Enhancing Robustness Against Noise and Outliers
M. Sajid
A. K. Malik
M. Tanveer
72
19
0
15 Jul 2023
Distributed Semi-Supervised Sparse Statistical Inference
Distributed Semi-Supervised Sparse Statistical Inference
Jiyuan Tu
Weidong Liu
Xiaojun Mao
Mingyue Xu
43
1
0
17 Jun 2023
Batches Stabilize the Minimum Norm Risk in High Dimensional
  Overparameterized Linear Regression
Batches Stabilize the Minimum Norm Risk in High Dimensional Overparameterized Linear Regression
Shahar Stein Ioushua
Inbar Hasidim
O. Shayevitz
M. Feder
61
0
0
14 Jun 2023
Lp- and Risk Consistency of Localized SVMs
Lp- and Risk Consistency of Localized SVMs
Hannes Köhler
117
0
0
16 May 2023
Distributed Gradient Descent for Functional Learning
Distributed Gradient Descent for Functional Learning
Zhan Yu
Jun Fan
Zhongjie Shi
Ding-Xuan Zhou
61
3
0
12 May 2023
A review of distributed statistical inference
A review of distributed statistical inference
Yuan Gao
Weidong Liu
Hansheng Wang
Xiaozhou Wang
Yibo Yan
Riquan Zhang
74
43
0
13 Apr 2023
On the Optimality of Misspecified Spectral Algorithms
On the Optimality of Misspecified Spectral Algorithms
Hao Zhang
Yicheng Li
Qian Lin
79
18
0
27 Mar 2023
Sketching with Spherical Designs for Noisy Data Fitting on Spheres
Sketching with Spherical Designs for Noisy Data Fitting on Spheres
Shao-Bo Lin
Di Wang
Ding-Xuan Zhou
57
2
0
08 Mar 2023
Kernel-Based Distributed Q-Learning: A Scalable Reinforcement Learning Approach for Dynamic Treatment Regimes
Kernel-Based Distributed Q-Learning: A Scalable Reinforcement Learning Approach for Dynamic Treatment Regimes
Di Wang
Yao Wang
Shaojie Tang
OffRL
143
1
0
21 Feb 2023
An Analysis of Attention via the Lens of Exchangeability and Latent
  Variable Models
An Analysis of Attention via the Lens of Exchangeability and Latent Variable Models
Yufeng Zhang
Boyi Liu
Qi Cai
Lingxiao Wang
Zhaoran Wang
121
13
0
30 Dec 2022
A Decentralized Framework for Kernel PCA with Projection Consensus
  Constraints
A Decentralized Framework for Kernel PCA with Projection Consensus Constraints
Fan He
Ruikai Yang
Lei Shi
Xiaolin Huang
81
2
0
29 Nov 2022
Statistical Optimality of Divide and Conquer Kernel-based Functional
  Linear Regression
Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression
Jiading Liu
Lei Shi
85
12
0
20 Nov 2022
Local SGD in Overparameterized Linear Regression
Local SGD in Overparameterized Linear Regression
Mike Nguyen
Charly Kirst
Nicole Mücke
58
0
0
20 Oct 2022
Distributed Estimation and Inference for Semi-parametric Binary Response
  Models
Distributed Estimation and Inference for Semi-parametric Binary Response Models
Xinyu Chen
Wenbo Jing
Weidong Liu
Yichen Zhang
47
2
0
15 Oct 2022
Communication-efficient Distributed Newton-like Optimization with
  Gradients and M-estimators
Communication-efficient Distributed Newton-like Optimization with Gradients and M-estimators
Ziyan Yin
77
0
0
13 Jul 2022
Federated Data Analytics: A Study on Linear Models
Federated Data Analytics: A Study on Linear Models
Xubo Yue
Raed Al Kontar
Ana María Estrada Gómez
FedML
79
14
0
15 Jun 2022
DDAC-SpAM: A Distributed Algorithm for Fitting High-dimensional Sparse
  Additive Models with Feature Division and Decorrelation
DDAC-SpAM: A Distributed Algorithm for Fitting High-dimensional Sparse Additive Models with Feature Division and Decorrelation
Yifan He
Ruiyang Wu
Yong Zhou
Yang Feng
59
1
0
16 May 2022
Global Bias-Corrected Divide-and-Conquer by Quantile-Matched Composite
  for General Nonparametric Regressions
Global Bias-Corrected Divide-and-Conquer by Quantile-Matched Composite for General Nonparametric Regressions
Yan Chen
Lu Lin
22
0
0
29 Jan 2022
Smooth Nested Simulation: Bridging Cubic and Square Root Convergence
  Rates in High Dimensions
Smooth Nested Simulation: Bridging Cubic and Square Root Convergence Rates in High Dimensions
Wei Cao
Yanyuan Wang
Xiaowei Zhang
19
5
0
09 Jan 2022
Markov subsampling based Huber Criterion
Markov subsampling based Huber Criterion
Tieliang Gong
Yuxin Dong
Hong Chen
B. Dong
Chen Li
55
2
0
12 Dec 2021
Radial Basis Function Approximation with Distributively Stored Data on
  Spheres
Radial Basis Function Approximation with Distributively Stored Data on Spheres
Han Feng
Shao-Bo Lin
Ding-Xuan Zhou
19
8
0
05 Dec 2021
Dynamic Regret for Strongly Adaptive Methods and Optimality of Online
  KRR
Dynamic Regret for Strongly Adaptive Methods and Optimality of Online KRR
Dheeraj Baby
Hilaf Hasson
Yuyang Wang
78
3
0
22 Nov 2021
Nyström Regularization for Time Series Forecasting
Nyström Regularization for Time Series Forecasting
Zirui Sun
Mingwei Dai
Yao Wang
Shao-Bo Lin
AI4TS
73
2
0
13 Nov 2021
Communication-Constrained Distributed Quantile Regression with Optimal
  Statistical Guarantees
Communication-Constrained Distributed Quantile Regression with Optimal Statistical Guarantees
Kean Ming Tan
Heather Battey
Wen-Xin Zhou
44
23
0
25 Oct 2021
Quantifying Epistemic Uncertainty in Deep Learning
Quantifying Epistemic Uncertainty in Deep Learning
Ziyi Huang
Henry Lam
Haofeng Zhang
UQCVBDLUDPER
112
14
0
23 Oct 2021
Data splitting improves statistical performance in overparametrized
  regimes
Data splitting improves statistical performance in overparametrized regimes
Nicole Mücke
Enrico Reiss
Jonas Rungenhagen
Markus Klein
55
8
0
21 Oct 2021
Sharp Analysis of Random Fourier Features in Classification
Sharp Analysis of Random Fourier Features in Classification
Zhu Li
64
6
0
22 Sep 2021
StreaMRAK a Streaming Multi-Resolution Adaptive Kernel Algorithm
StreaMRAK a Streaming Multi-Resolution Adaptive Kernel Algorithm
Andreas Oslandsbotn
Ž. Kereta
Valeriya Naumova
Y. Freund
A. Cloninger
39
2
0
23 Aug 2021
Fast Sketching of Polynomial Kernels of Polynomial Degree
Fast Sketching of Polynomial Kernels of Polynomial Degree
Zhao Song
David P. Woodruff
Zheng Yu
Lichen Zhang
82
41
0
21 Aug 2021
Intrinsic Dimension Adaptive Partitioning for Kernel Methods
Intrinsic Dimension Adaptive Partitioning for Kernel Methods
Thomas Hamm
Ingo Steinwart
28
3
0
16 Jul 2021
Oversampling Divide-and-conquer for Response-skewed Kernel Ridge
  Regression
Oversampling Divide-and-conquer for Response-skewed Kernel Ridge Regression
Jingyi Zhang
Xiaoxiao Sun
46
0
0
13 Jul 2021
ParK: Sound and Efficient Kernel Ridge Regression by Feature Space
  Partitions
ParK: Sound and Efficient Kernel Ridge Regression by Feature Space Partitions
Luigi Carratino
Stefano Vigogna
Daniele Calandriello
Lorenzo Rosasco
55
7
0
23 Jun 2021
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