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Additive Models with Trend Filtering
v1v2v3v4 (latest)

Additive Models with Trend Filtering

16 February 2017
Veeranjaneyulu Sadhanala
Robert Tibshirani
ArXiv (abs)PDFHTML

Papers citing "Additive Models with Trend Filtering"

10 / 10 papers shown
Title
Variance estimation in graphs with the fused lasso
Variance estimation in graphs with the fused lasso
Oscar Hernan Madrid Padilla
170
5
0
26 Jul 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
68
1
0
16 May 2022
A cautionary tale on fitting decision trees to data from additive
  models: generalization lower bounds
A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds
Yan Shuo Tan
Abhineet Agarwal
Bin Yu
79
11
0
18 Oct 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand
  Challenges
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges
Cynthia Rudin
Chaofan Chen
Zhi Chen
Haiyang Huang
Lesia Semenova
Chudi Zhong
FaMLAI4CELRM
245
677
0
20 Mar 2021
Tensor denoising with trend filtering
Tensor denoising with trend filtering
Francesco Ortelli
Sara van de Geer
72
5
0
26 Jan 2021
Risk Bounds for Quantile Trend Filtering
Risk Bounds for Quantile Trend Filtering
Oscar Hernan Madrid Padilla
S. Chatterjee
88
22
0
15 Jul 2020
How Interpretable and Trustworthy are GAMs?
How Interpretable and Trustworthy are GAMs?
C. Chang
S. Tan
Benjamin J. Lengerich
Anna Goldenberg
R. Caruana
FAtt
127
80
0
11 Jun 2020
Hierarchical Total Variations and Doubly Penalized ANOVA Modeling for
  Multivariate Nonparametric Regression
Hierarchical Total Variations and Doubly Penalized ANOVA Modeling for Multivariate Nonparametric Regression
Ting Yang
Zhiqiang Tan
50
2
0
16 Jun 2019
An analysis of the cost of hyper-parameter selection via split-sample
  validation, with applications to penalized regression
An analysis of the cost of hyper-parameter selection via split-sample validation, with applications to penalized regression
Jean Feng
N. Simon
66
2
0
28 Mar 2019
Dykstra's Algorithm, ADMM, and Coordinate Descent: Connections,
  Insights, and Extensions
Dykstra's Algorithm, ADMM, and Coordinate Descent: Connections, Insights, and Extensions
Robert Tibshirani
111
43
0
12 May 2017
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