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A Partially Linear Framework for Massive Heterogeneous Data
v1v2 (latest)

A Partially Linear Framework for Massive Heterogeneous Data

30 October 2014
Tianqi Zhao
Guang Cheng
Han Liu
ArXiv (abs)PDFHTML

Papers citing "A Partially Linear Framework for Massive Heterogeneous Data"

45 / 45 papers shown
Title
Multi-task Learning for Heterogeneous Multi-source Block-Wise Missing Data
Multi-task Learning for Heterogeneous Multi-source Block-Wise Missing Data
Yang Sui
Qi Xu
Y. Bai
Annie Qu
49
2
0
30 May 2025
DCNN: Dual Cross-current Neural Networks Realized Using An Interactive
  Deep Learning Discriminator for Fine-grained Objects
DCNN: Dual Cross-current Neural Networks Realized Using An Interactive Deep Learning Discriminator for Fine-grained Objects
Da Fu
Mingfei Rong
Eun-Hu Kim
Hao Huang
Witold Pedrycz
112
0
0
07 May 2024
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
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
Approximating Partial Likelihood Estimators via Optimal Subsampling
Approximating Partial Likelihood Estimators via Optimal Subsampling
Haixiang Zhang
Lulu Zuo
Haiying Wang
Liuquan Sun
60
14
0
10 Oct 2022
Heterogeneous Federated Learning on a Graph
Heterogeneous Federated Learning on a Graph
Huiyuan Wang
Xuyang Zhao
Weijie Lin
FedML
107
4
0
19 Sep 2022
Weighted Distributed Estimation under Heterogeneity
Weighted Distributed Estimation under Heterogeneity
J. Gu
Songxi Chen
27
1
0
14 Sep 2022
Multiple Descent in the Multiple Random Feature Model
Multiple Descent in the Multiple Random Feature Model
Xuran Meng
Jianfeng Yao
Yuan Cao
78
7
0
21 Aug 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
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
Variance Reduced Median-of-Means Estimator for Byzantine-Robust
  Distributed Inference
Variance Reduced Median-of-Means Estimator for Byzantine-Robust Distributed Inference
Jiyuan Tu
Weidong Liu
Xiaojun Mao
Xi Chen
51
20
0
04 Mar 2021
Divide-and-conquer methods for big data analysis
Divide-and-conquer methods for big data analysis
Xueying Chen
Jerry Q. Cheng
Min‐ge Xie
44
9
0
22 Feb 2021
Distributed Bootstrap for Simultaneous Inference Under High
  Dimensionality
Distributed Bootstrap for Simultaneous Inference Under High Dimensionality
Yang Yu
Shih-Kang Chao
Guang Cheng
FedML
75
10
0
19 Feb 2021
Statistical Inference for Maximin Effects: Identifying Stable
  Associations across Multiple Studies
Statistical Inference for Maximin Effects: Identifying Stable Associations across Multiple Studies
Zijian Guo
56
17
0
15 Nov 2020
Distributed Estimation for Principal Component Analysis: an Enlarged
  Eigenspace Analysis
Distributed Estimation for Principal Component Analysis: an Enlarged Eigenspace Analysis
Xi Chen
Jason D. Lee
He Li
Yun Yang
79
6
0
05 Apr 2020
Simultaneous Inference for Massive Data: Distributed Bootstrap
Simultaneous Inference for Massive Data: Distributed Bootstrap
Yang Yu
Shih-Kang Chao
Guang Cheng
FedML
48
15
0
19 Feb 2020
Off-Policy Estimation of Long-Term Average Outcomes with Applications to
  Mobile Health
Off-Policy Estimation of Long-Term Average Outcomes with Applications to Mobile Health
Peng Liao
P. Klasnja
Susan Murphy
OffRL
85
68
0
30 Dec 2019
Heterogeneity-aware and communication-efficient distributed statistical
  inference
Heterogeneity-aware and communication-efficient distributed statistical inference
R. Duan
Y. Ning
Yong Chen
58
70
0
20 Dec 2019
Rates of Convergence for Large-scale Nearest Neighbor Classification
Rates of Convergence for Large-scale Nearest Neighbor Classification
Xingye Qiao
Jiexin Duan
Guang Cheng
57
9
0
03 Sep 2019
Distributed High-dimensional Regression Under a Quantile Loss Function
Distributed High-dimensional Regression Under a Quantile Loss Function
Xi Chen
Weidong Liu
Xiaojun Mao
Zhuoyi Yang
72
72
0
13 Jun 2019
A Global Bias-Correction DC Method for Biased Estimation under Memory
  Constraint
A Global Bias-Correction DC Method for Biased Estimation under Memory Constraint
Lu Lin
Feng Li
40
2
0
16 Apr 2019
WONDER: Weighted one-shot distributed ridge regression in high
  dimensions
WONDER: Weighted one-shot distributed ridge regression in high dimensions
Yan Sun
Yueqi Sheng
OffRL
92
51
0
22 Mar 2019
Smoothing Spline Semiparametric Density Models
Smoothing Spline Semiparametric Density Models
J. Shi
Jiahui Yu
Anna Liu
Yuedong Wang
40
6
0
10 Jan 2019
Distributed Nearest Neighbor Classification
Distributed Nearest Neighbor Classification
Jiexin Duan
Xingye Qiao
Guang Cheng
21
4
0
12 Dec 2018
Distributed Inference for Linear Support Vector Machine
Distributed Inference for Linear Support Vector Machine
Xiaozhou Wang
Zhuoyi Yang
Xi Chen
Weidong Liu
100
65
0
29 Nov 2018
First-order Newton-type Estimator for Distributed Estimation and
  Inference
First-order Newton-type Estimator for Distributed Estimation and Inference
Xi Chen
Weidong Liu
Yichen Zhang
97
51
0
28 Nov 2018
Quantile Regression Under Memory Constraint
Quantile Regression Under Memory Constraint
Xi Chen
Weidong Liu
Yichen Zhang
99
119
0
18 Oct 2018
Distributed linear regression by averaging
Distributed linear regression by averaging
Yan Sun
Yueqi Sheng
FedML
94
66
0
30 Sep 2018
Removing the Curse of Superefficiency: an Effective Strategy For
  Distributed Computing in Isotonic Regression
Removing the Curse of Superefficiency: an Effective Strategy For Distributed Computing in Isotonic Regression
Moulinath Banerjee
C. Durot
50
1
0
22 Jun 2018
How Many Machines Can We Use in Parallel Computing for Kernel Ridge
  Regression?
How Many Machines Can We Use in Parallel Computing for Kernel Ridge Regression?
Meimei Liu
Zuofeng Shang
Guang Cheng
47
8
0
25 May 2018
Statistical Validity and Consistency of Big Data Analytics: A General
  Framework
Statistical Validity and Consistency of Big Data Analytics: A General Framework
B. Karmakar
I. Mukhopadhyay
26
1
0
29 Mar 2018
Statistical Inference on Panel Data Models: A Kernel Ridge Regression
  Method
Statistical Inference on Panel Data Models: A Kernel Ridge Regression Method
Shunan Zhao
Ruiqi Liu
Zuofeng Shang
27
11
0
08 Mar 2017
Distributed inference for quantile regression processes
Distributed inference for quantile regression processes
S. Volgushev
Shih-Kang Chao
Guang Cheng
546
131
0
21 Jan 2017
Additive Partially Linear Models for Massive Heterogeneous Data
Additive Partially Linear Models for Massive Heterogeneous Data
Binhuan Wang
Yixin Fang
Heng Lian
Hua Liang
64
5
0
13 Jan 2017
Efficient Distributed Learning with Sparsity
Efficient Distributed Learning with Sparsity
Jialei Wang
Mladen Kolar
Nathan Srebro
Tong Zhang
FedML
90
152
0
25 May 2016
A Massive Data Framework for M-Estimators with Cubic-Rate
A Massive Data Framework for M-Estimators with Cubic-Rate
C. Shi
Wenbin Lu
Rui Song
272
74
0
24 May 2016
Divide and Conquer in Non-standard Problems and the Super-efficiency
  Phenomenon
Divide and Conquer in Non-standard Problems and the Super-efficiency Phenomenon
Moulinath Banerjee
C. Durot
B. Sen
301
64
0
14 May 2016
Quantile Processes for Semi and Nonparametric Regression
Quantile Processes for Semi and Nonparametric Regression
Shih-Kang Chao
S. Volgushev
Guang Cheng
319
25
0
07 Apr 2016
Nonparametric Heterogeneity Testing For Massive Data
Nonparametric Heterogeneity Testing For Massive Data
Junwei Lu
Guang Cheng
Han Liu
55
19
0
23 Jan 2016
Distributed Bayesian Learning with Stochastic Natural-gradient
  Expectation Propagation and the Posterior Server
Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server
Leonard Hasenclever
Stefan Webb
Thibaut Lienart
Sebastian J. Vollmer
Balaji Lakshminarayanan
Charles Blundell
Yee Whye Teh
BDL
183
70
0
31 Dec 2015
Computational Limits of A Distributed Algorithm For Smoothing Spline
Computational Limits of A Distributed Algorithm For Smoothing Spline
Zuofeng Shang
Guang Cheng
261
56
0
31 Dec 2015
A Distributed One-Step Estimator
A Distributed One-Step Estimator
Cheng Huang
X. Huo
FedML
124
84
0
04 Nov 2015
Distributed Estimation and Inference with Statistical Guarantees
Distributed Estimation and Inference with Statistical Guarantees
Heather Battey
Jianqing Fan
Han Liu
Junwei Lu
Ziwei Zhu
88
83
0
17 Sep 2015
Nonparametric Bayesian Aggregation for Massive Data
Nonparametric Bayesian Aggregation for Massive Data
Zuofeng Shang
Botao Hao
Guang Cheng
22
8
0
17 Aug 2015
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