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Elastic-Net Regularization in Learning Theory

Elastic-Net Regularization in Learning Theory

Journal of Complexity (JC), 2008
22 July 2008
C. D. Mol
Ernesto De Vito
Lorenzo Rosasco
    OODCML
ArXiv (abs)PDFHTML

Papers citing "Elastic-Net Regularization in Learning Theory"

33 / 33 papers shown
AI-based modular warning machine for risk identification in proximity healthcare
AI-based modular warning machine for risk identification in proximity healthcare
Chiara Razzetta
Shahryar Noei
Federico Barbarossa
Edoardo Spairani
Monica Roascio
...
A. Massone
F. Benvenuto
Giuseppe Jurman
Diego Sona
C. Campi
166
0
0
13 Jun 2025
An evolutionary approach for discovering non-Gaussian stochastic
  dynamical systems based on nonlocal Kramers-Moyal formulas
An evolutionary approach for discovering non-Gaussian stochastic dynamical systems based on nonlocal Kramers-Moyal formulas
Yang Li
Shengyuan Xu
Jinqiao Duan
212
1
0
29 Sep 2024
Learning with Norm Constrained, Over-parameterized, Two-layer Neural
  Networks
Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks
Fanghui Liu
L. Dadi
Volkan Cevher
495
10
0
29 Apr 2024
Applied Causal Inference Powered by ML and AI
Applied Causal Inference Powered by ML and AI
Victor Chernozhukov
Christian Hansen
Nathan Kallus
Martin Spindler
Vasilis Syrgkanis
CML
438
57
0
04 Mar 2024
Learned reconstruction methods for inverse problems: sample error
  estimates
Learned reconstruction methods for inverse problems: sample error estimates
Luca Ratti
275
1
0
21 Dec 2023
Consensus Function from an $L_p^q-$norm Regularization Term for its Use
  as Adaptive Activation Functions in Neural Networks
Consensus Function from an Lpq−L_p^q-Lpq​−norm Regularization Term for its Use as Adaptive Activation Functions in Neural Networks
Juan Heredia Juesas
José Á. Martínez-Lorenzo
167
0
0
30 Jun 2022
Minimax risk classifiers with 0-1 loss
Minimax risk classifiers with 0-1 lossJournal of machine learning research (JMLR), 2022
Santiago Mazuelas
Mauricio Romero
Peter Grünwald
674
9
0
17 Jan 2022
Road Roughness Estimation Using Machine Learning
Road Roughness Estimation Using Machine Learning
M. Bajic
Shahrzad M. Pour
A. Skar
M. Pettinari
E. Levenberg
T. S. Alstrøm
110
11
0
02 Jul 2021
Kernel regression in high dimensions: Refined analysis beyond double
  descent
Kernel regression in high dimensions: Refined analysis beyond double descent
Fanghui Liu
Zhenyu Liao
Johan A. K. Suykens
445
49
0
06 Oct 2020
Generalized Maximum Entropy for Supervised Classification
Generalized Maximum Entropy for Supervised ClassificationIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Santiago Mazuelas
Yuan-Chung Shen
Aritz Pérez
466
39
0
10 Jul 2020
Interpolation and Learning with Scale Dependent Kernels
Nicolò Pagliana
Alessandro Rudi
Ernesto De Vito
Lorenzo Rosasco
416
8
0
17 Jun 2020
On the robustness of the minimum $\ell_2$ interpolator
On the robustness of the minimum ℓ2\ell_2ℓ2​ interpolator
Geoffrey Chinot
M. Lerasle
215
10
0
12 Mar 2020
Boltzmann machine learning and regularization methods for inferring
  evolutionary fields and couplings from a multiple sequence alignment
Boltzmann machine learning and regularization methods for inferring evolutionary fields and couplings from a multiple sequence alignmentIEEE/ACM Transactions on Computational Biology & Bioinformatics (TCBB), 2019
S. Miyazawa
272
1
0
10 Sep 2019
Sparse Learning for Variable Selection with Structures and
  Nonlinearities
Sparse Learning for Variable Selection with Structures and Nonlinearities
Magda Gregorova
364
1
0
26 Mar 2019
High-dimensional semi-supervised learning: in search for optimal
  inference of the mean
High-dimensional semi-supervised learning: in search for optimal inference of the mean
Yuqian Zhang
Jelena Bradic
195
34
0
02 Feb 2019
Elastic-net Regularized High-dimensional Negative Binomial Regression:
  Consistency and Weak Signals Detection
Elastic-net Regularized High-dimensional Negative Binomial Regression: Consistency and Weak Signals Detection
Huiming Zhang
Jinzhu Jia
508
38
0
09 Dec 2017
Universal Consistency and Robustness of Localized Support Vector
  Machines
Universal Consistency and Robustness of Localized Support Vector Machines
Florian Dumpert
301
18
0
19 Mar 2017
Variable Selection with Scalable Bootstrap in Generalized Linear Model
  for Massive Data
Variable Selection with Scalable Bootstrap in Generalized Linear Model for Massive Data
Zhibing He
Yichen Qin
B. Shia
Yang Li
138
0
0
06 Dec 2016
Generalized Kalman Smoothing: Modeling and Algorithms
Generalized Kalman Smoothing: Modeling and Algorithms
Aleksandr Aravkin
J. Burke
L. Ljung
A. Lozano
G. Pillonetto
432
126
0
20 Sep 2016
Boosting as a kernel-based method
Boosting as a kernel-based method
Aleksandr Aravkin
Giulio Bottegal
G. Pillonetto
318
9
0
08 Aug 2016
Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace
  Clustering
Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering
Chong You
Chun-Guang Li
Daniel P. Robinson
René Vidal
362
263
0
09 May 2016
A short note on extension theorems and their connection to universal
  consistency in machine learning
A short note on extension theorems and their connection to universal consistency in machine learning
A. Christmann
Florian Dumpert
Daohong Xiang
242
2
0
15 Apr 2016
Generalized support vector regression: duality and tensor-kernel
  representation
Generalized support vector regression: duality and tensor-kernel representation
Saverio Salzo
Johan A. K. Suykens
278
9
0
18 Mar 2016
Generalized conditional gradient: analysis of convergence and
  applications
Generalized conditional gradient: analysis of convergence and applications
A. Rakotomamonjy
Rémi Flamary
Nicolas Courty
233
23
0
22 Oct 2015
Consistent Learning by Composite Proximal Thresholding
Consistent Learning by Composite Proximal Thresholding
P. Combettes
Saverio Salzo
S. Villa
351
15
0
17 Apr 2015
Characterization of the equivalence of robustification and
  regularization in linear and matrix regression
Characterization of the equivalence of robustification and regularization in linear and matrix regression
Dimitris Bertsimas
M. Copenhaver
OOD
430
13
0
22 Nov 2014
Regularized Learning Schemes in Feature Banach Spaces
Regularized Learning Schemes in Feature Banach Spaces
P. Combettes
Saverio Salzo
S. Villa
316
17
0
24 Oct 2014
Performance Analysis Of Regularized Linear Regression Models For
  Oxazolines And Oxazoles Derivitive Descriptor Dataset
Performance Analysis Of Regularized Linear Regression Models For Oxazolines And Oxazoles Derivitive Descriptor Dataset
Doreswamy
C. Vastrad
OOD
195
13
0
10 Dec 2013
Sparse Predictive Structure of Deconvolved Functional Brain Networks
Sparse Predictive Structure of Deconvolved Functional Brain Networks
Tommaso Furlanello
M. Cristoforetti
Cesare Furlanello
Giuseppe Jurman
184
5
0
24 Oct 2013
Generalized system identification with stable spline kernels
Generalized system identification with stable spline kernels
Aleksandr Aravkin
J. Burke
G. Pillonetto
373
6
0
30 Sep 2013
Sparse Prediction with the $k$-Support Norm
Sparse Prediction with the kkk-Support NormNeural Information Processing Systems (NeurIPS), 2012
Andreas Argyriou
Rina Foygel
Nathan Srebro
389
163
0
23 Apr 2012
Learning Sets with Separating Kernels
Learning Sets with Separating Kernels
Ernesto De Vito
Lorenzo Rosasco
A. Toigo
292
57
0
16 Apr 2012
Structured Sparsity and Generalization
Structured Sparsity and Generalization
Andreas Maurer
Massimiliano Pontil
437
63
0
17 Aug 2011
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