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The Theory Behind Overfitting, Cross Validation, Regularization,
  Bagging, and Boosting: Tutorial

The Theory Behind Overfitting, Cross Validation, Regularization, Bagging, and Boosting: Tutorial

28 May 2019
Benyamin Ghojogh
Mark Crowley
    AI4CE
ArXivPDFHTML

Papers citing "The Theory Behind Overfitting, Cross Validation, Regularization, Bagging, and Boosting: Tutorial"

7 / 7 papers shown
Title
Testing for Overfitting
Testing for Overfitting
J. Schmidt
21
2
0
09 May 2023
Sampling Algorithms, from Survey Sampling to Monte Carlo Methods:
  Tutorial and Literature Review
Sampling Algorithms, from Survey Sampling to Monte Carlo Methods: Tutorial and Literature Review
Benyamin Ghojogh
Hadi Nekoei
Aydin Ghojogh
Fakhri Karray
Mark Crowley
22
14
0
02 Nov 2020
Dataset Augmentation in Feature Space
Dataset Augmentation in Feature Space
Terrance Devries
Graham W. Taylor
64
428
0
17 Feb 2017
SSD: Single Shot MultiBox Detector
SSD: Single Shot MultiBox Detector
Wen Liu
Dragomir Anguelov
D. Erhan
Christian Szegedy
Scott E. Reed
Cheng-Yang Fu
Alexander C. Berg
ObjD
BDL
229
29,816
0
08 Dec 2015
Optimization with Sparsity-Inducing Penalties
Optimization with Sparsity-Inducing Penalties
Francis R. Bach
Rodolphe Jenatton
Julien Mairal
G. Obozinski
209
1,058
0
03 Aug 2011
On the Doubt about Margin Explanation of Boosting
On the Doubt about Margin Explanation of Boosting
Wei Gao
Zhi Zhou
UQCV
75
180
0
19 Sep 2010
A survey of cross-validation procedures for model selection
A survey of cross-validation procedures for model selection
Sylvain Arlot
Alain Celisse
205
3,594
0
27 Jul 2009
1