ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1108.0775
  4. Cited By
Optimization with Sparsity-Inducing Penalties

Optimization with Sparsity-Inducing Penalties

3 August 2011
Francis R. Bach
Rodolphe Jenatton
Julien Mairal
G. Obozinski
ArXivPDFHTML

Papers citing "Optimization with Sparsity-Inducing Penalties"

50 / 94 papers shown
Title
Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries
Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries
Chris Kolb
T. Weber
Bernd Bischl
David Rügamer
113
0
0
04 Feb 2025
Piecewise Ruled Approximation for Freeform Mesh Surfaces
Piecewise Ruled Approximation for Freeform Mesh Surfaces
Yiling Pan
Zhixin Xu
Bin Wang
Bailin Deng
AI4CE
53
0
0
25 Jan 2025
Training a neural netwok for data reduction and better generalization
Training a neural netwok for data reduction and better generalization
S. Sardy
Maxime van Cutsem
Xiaoyu Ma
MLT
69
0
0
26 Nov 2024
Efficient Optimization Algorithms for Linear Adversarial Training
Efficient Optimization Algorithms for Linear Adversarial Training
Antônio H. Ribeiro
Thomas B. Schon
Dave Zahariah
Francis Bach
AAML
45
1
0
16 Oct 2024
Evaluating Model Robustness Using Adaptive Sparse L0 Regularization
Evaluating Model Robustness Using Adaptive Sparse L0 Regularization
Weiyou Liu
Zhenyang Li
Weitong Chen
AAML
30
1
0
28 Aug 2024
Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models
Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models
Jeremy E. Cohen
Valentin Leplat
63
1
0
27 Mar 2024
Assigning Stationary Distributions to Sparse Stochastic Matrices
Assigning Stationary Distributions to Sparse Stochastic Matrices
Nicolas Gillis
P. Dooren
10
2
0
26 Dec 2023
Nonparametric Linear Feature Learning in Regression Through
  Regularisation
Nonparametric Linear Feature Learning in Regression Through Regularisation
Bertille Follain
Francis R. Bach
23
3
0
24 Jul 2023
Sparse Graphical Linear Dynamical Systems
Sparse Graphical Linear Dynamical Systems
Émilie Chouzenoux
Victor Elvira
25
7
0
06 Jul 2023
First Order Methods with Markovian Noise: from Acceleration to
  Variational Inequalities
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities
Aleksandr Beznosikov
S. Samsonov
Marina Sheshukova
Alexander Gasnikov
A. Naumov
Eric Moulines
39
14
0
25 May 2023
Similarity, Compression and Local Steps: Three Pillars of Efficient
  Communications for Distributed Variational Inequalities
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities
Aleksandr Beznosikov
Martin Takáč
Alexander Gasnikov
29
10
0
15 Feb 2023
Dual-sPLS: a family of Dual Sparse Partial Least Squares regressions for
  feature selection and prediction with tunable sparsity; evaluation on
  simulated and near-infrared (NIR) data
Dual-sPLS: a family of Dual Sparse Partial Least Squares regressions for feature selection and prediction with tunable sparsity; evaluation on simulated and near-infrared (NIR) data
Louna Alsouki
L. Duval
C. Marteau
Rami El Haddad
Franccois Wahl
14
7
0
17 Jan 2023
Regression as Classification: Influence of Task Formulation on Neural
  Network Features
Regression as Classification: Influence of Task Formulation on Neural Network Features
Lawrence Stewart
Francis R. Bach
Quentin Berthet
Jean-Philippe Vert
27
24
0
10 Nov 2022
Quantized Compressed Sensing with Score-based Generative Models
Quantized Compressed Sensing with Score-based Generative Models
Xiangming Meng
Y. Kabashima
DiffM
24
11
0
02 Nov 2022
Outlier-Insensitive Kalman Filtering Using NUV Priors
Outlier-Insensitive Kalman Filtering Using NUV Priors
Shunit Truzman
Guy Revach
Nir Shlezinger
Itzik Klein
23
3
0
12 Oct 2022
High-resolution Face Swapping via Latent Semantics Disentanglement
High-resolution Face Swapping via Latent Semantics Disentanglement
Yangyang Xu
Bailin Deng
Junle Wang
Yanqing Jing
Jianxiong Pan
Shengfeng He
CVBM
PICV
30
75
0
30 Mar 2022
Stability and Risk Bounds of Iterative Hard Thresholding
Stability and Risk Bounds of Iterative Hard Thresholding
Xiao-Tong Yuan
P. Li
37
12
0
17 Mar 2022
Energy-Latency Attacks via Sponge Poisoning
Energy-Latency Attacks via Sponge Poisoning
Antonio Emanuele Cinà
Ambra Demontis
Battista Biggio
Fabio Roli
Marcello Pelillo
SILM
42
29
0
14 Mar 2022
Alternative design of DeepPDNet in the context of image restoration
Alternative design of DeepPDNet in the context of image restoration
Mingyuan Jiu
N. Pustelnik
27
2
0
20 Feb 2022
Optimal Algorithms for Decentralized Stochastic Variational Inequalities
Optimal Algorithms for Decentralized Stochastic Variational Inequalities
D. Kovalev
Aleksandr Beznosikov
Abdurakhmon Sadiev
Michael Persiianov
Peter Richtárik
Alexander Gasnikov
35
34
0
06 Feb 2022
A Stochastic Bundle Method for Interpolating Networks
A Stochastic Bundle Method for Interpolating Networks
Alasdair Paren
Leonard Berrada
Rudra P. K. Poudel
M. P. Kumar
24
4
0
29 Jan 2022
Stable Conformal Prediction Sets
Stable Conformal Prediction Sets
Eugène Ndiaye
35
20
0
19 Dec 2021
Safe rules for the identification of zeros in the solutions of the SLOPE
  problem
Safe rules for the identification of zeros in the solutions of the SLOPE problem
Clément Elvira
Cédric Herzet
33
9
0
22 Oct 2021
High-Dimensional Quantile Regression: Convolution Smoothing and Concave
  Regularization
High-Dimensional Quantile Regression: Convolution Smoothing and Concave Regularization
Kean Ming Tan
Lan Wang
Wen-Xin Zhou
29
56
0
12 Sep 2021
Smooth Bilevel Programming for Sparse Regularization
Smooth Bilevel Programming for Sparse Regularization
C. Poon
Gabriel Peyré
11
18
0
02 Jun 2021
Root-finding Approaches for Computing Conformal Prediction Set
Root-finding Approaches for Computing Conformal Prediction Set
Eugène Ndiaye
Ichiro Takeuchi
23
10
0
14 Apr 2021
Expanding boundaries of Gap Safe screening
Expanding boundaries of Gap Safe screening
C. Dantas
Emmanuel Soubies
Cédric Févotte
13
16
0
22 Feb 2021
Decentralized Distributed Optimization for Saddle Point Problems
Decentralized Distributed Optimization for Saddle Point Problems
Alexander Rogozin
Alexander Beznosikov
D. Dvinskikh
D. Kovalev
Pavel Dvurechensky
Alexander Gasnikov
28
27
0
15 Feb 2021
The Nonconvex Geometry of Linear Inverse Problems
The Nonconvex Geometry of Linear Inverse Problems
Armin Eftekhari
Peyman Mohajerin Esfahani
15
1
0
07 Jan 2021
Sequential convergence of AdaGrad algorithm for smooth convex
  optimization
Sequential convergence of AdaGrad algorithm for smooth convex optimization
Cheik Traoré
Edouard Pauwels
11
21
0
24 Nov 2020
Robust Compressed Sensing using Generative Models
Robust Compressed Sensing using Generative Models
A. Jalal
Liu Liu
A. Dimakis
C. Caramanis
21
39
0
16 Jun 2020
Determined BSS based on time-frequency masking and its application to
  harmonic vector analysis
Determined BSS based on time-frequency masking and its application to harmonic vector analysis
Kohei Yatabe
Daichi Kitamura
21
26
0
29 Apr 2020
Deep Randomized Neural Networks
Deep Randomized Neural Networks
Claudio Gallicchio
Simone Scardapane
OOD
41
61
0
27 Feb 2020
Sparse Optimization for Green Edge AI Inference
Sparse Optimization for Green Edge AI Inference
Xiangyu Yang
Sheng Hua
Yuanming Shi
Hao Wang
Jun Zhang
Khaled B. Letaief
19
14
0
24 Feb 2020
Learning with Differentiable Perturbed Optimizers
Learning with Differentiable Perturbed Optimizers
Quentin Berthet
Mathieu Blondel
O. Teboul
Marco Cuturi
Jean-Philippe Vert
Francis R. Bach
29
105
0
20 Feb 2020
On the Effectiveness of Richardson Extrapolation in Machine Learning
On the Effectiveness of Richardson Extrapolation in Machine Learning
Francis R. Bach
13
9
0
07 Feb 2020
GraphEM: EM algorithm for blind Kalman filtering under graphical
  sparsity constraints
GraphEM: EM algorithm for blind Kalman filtering under graphical sparsity constraints
Émilie Chouzenoux
Victor Elvira
18
16
0
09 Jan 2020
Joint Graph-based Depth Refinement and Normal Estimation
Joint Graph-based Depth Refinement and Normal Estimation
Mattia Rossi
Mireille El Gheche
Andreas Kuhn
P. Frossard
3DV
14
21
0
03 Dec 2019
Multimodal Image Super-resolution via Deep Unfolding with Side
  Information
Multimodal Image Super-resolution via Deep Unfolding with Side Information
Iman Marivani
Evaggelia Tsiligianni
Bruno Cornelis
Nikos Deligiannis
SupR
26
17
0
18 Oct 2019
Computing Full Conformal Prediction Set with Approximate Homotopy
Computing Full Conformal Prediction Set with Approximate Homotopy
Eugène Ndiaye
Ichiro Takeuchi
19
15
0
20 Sep 2019
Energy-Efficient Processing and Robust Wireless Cooperative Transmission
  for Edge Inference
Energy-Efficient Processing and Robust Wireless Cooperative Transmission for Edge Inference
Kai Yang
Yuanming Shi
Wei Yu
Z. Ding
16
42
0
29 Jul 2019
Sparse Optimization on Measures with Over-parameterized Gradient Descent
Sparse Optimization on Measures with Over-parameterized Gradient Descent
Lénaïc Chizat
21
92
0
24 Jul 2019
Stochastic Iterative Hard Thresholding for Graph-structured Sparsity
  Optimization
Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization
Baojian Zhou
F. Chen
Yiming Ying
26
7
0
09 May 2019
Ising Models with Latent Conditional Gaussian Variables
Ising Models with Latent Conditional Gaussian Variables
Frank Nussbaum
Joachim Giesen
CML
17
6
0
28 Jan 2019
Task Embedded Coordinate Update: A Realizable Framework for Multivariate
  Non-convex Optimization
Task Embedded Coordinate Update: A Realizable Framework for Multivariate Non-convex Optimization
Yiyang Wang
Risheng Liu
Long Ma
Xiaoliang Song
22
2
0
05 Nov 2018
Nonconvex and Nonsmooth Sparse Optimization via Adaptively Iterative
  Reweighted Methods
Nonconvex and Nonsmooth Sparse Optimization via Adaptively Iterative Reweighted Methods
Hao Wang
Fan Zhang
Yuanming Shi
Yaohua Hu
11
28
0
24 Oct 2018
Compressed Sensing with Deep Image Prior and Learned Regularization
Compressed Sensing with Deep Image Prior and Learned Regularization
Dave Van Veen
A. Jalal
Mahdi Soltanolkotabi
Eric Price
S. Vishwanath
A. Dimakis
33
178
0
17 Jun 2018
Parallel and Distributed Successive Convex Approximation Methods for
  Big-Data Optimization
Parallel and Distributed Successive Convex Approximation Methods for Big-Data Optimization
G. Scutari
Ying Sun
35
61
0
17 May 2018
Sharp oracle inequalities for stationary points of nonconvex penalized
  M-estimators
Sharp oracle inequalities for stationary points of nonconvex penalized M-estimators
A. Elsener
Sara van de Geer
22
10
0
27 Feb 2018
ConvSCCS: convolutional self-controlled case series model for lagged
  adverse event detection
ConvSCCS: convolutional self-controlled case series model for lagged adverse event detection
Maryan Morel
Emmanuel Bacry
Stéphane Gaïffas
Agathe Guilloux
F. Leroy
19
14
0
21 Dec 2017
12
Next