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. 1410.5137
  4. Cited By
On Iterative Hard Thresholding Methods for High-dimensional M-Estimation

On Iterative Hard Thresholding Methods for High-dimensional M-Estimation

20 October 2014
Prateek Jain
Ambuj Tewari
Purushottam Kar
ArXivPDFHTML

Papers citing "On Iterative Hard Thresholding Methods for High-dimensional M-Estimation"

32 / 32 papers shown
Title
Tensor Methods in High Dimensional Data Analysis: Opportunities and
  Challenges
Tensor Methods in High Dimensional Data Analysis: Opportunities and Challenges
Arnab Auddy
Dong Xia
Ming Yuan
AI4CE
50
2
0
28 May 2024
Gradient Descent Converges Linearly for Logistic Regression on Separable
  Data
Gradient Descent Converges Linearly for Logistic Regression on Separable Data
Kyriakos Axiotis
M. Sviridenko
MLT
6
3
0
26 Jun 2023
Slow Kill for Big Data Learning
Slow Kill for Big Data Learning
Yiyuan She
Jianhui Shen
Adrian Barbu
30
3
0
02 May 2023
Score Attack: A Lower Bound Technique for Optimal Differentially Private
  Learning
Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning
T. Tony Cai
Yichen Wang
Linjun Zhang
46
16
0
13 Mar 2023
Understanding Best Subset Selection: A Tale of Two C(omplex)ities
Understanding Best Subset Selection: A Tale of Two C(omplex)ities
Saptarshi Roy
Ambuj Tewari
Ziwei Zhu
20
0
0
16 Jan 2023
Stochastic Mirror Descent for Large-Scale Sparse Recovery
Stochastic Mirror Descent for Large-Scale Sparse Recovery
Sasila Ilandarideva
Yannis Bekri
A. Juditsky
Vianney Perchet
25
1
0
23 Oct 2022
Convergence of the mini-batch SIHT algorithm
Convergence of the mini-batch SIHT algorithm
S. Damadi
Jinglai Shen
14
2
0
29 Sep 2022
Robust Methods for High-Dimensional Linear Learning
Robust Methods for High-Dimensional Linear Learning
Ibrahim Merad
Stéphane Gaïffas
OOD
50
3
0
10 Aug 2022
Stability and Risk Bounds of Iterative Hard Thresholding
Stability and Risk Bounds of Iterative Hard Thresholding
Xiao-Tong Yuan
P. Li
39
12
0
17 Mar 2022
AGGLIO: Global Optimization for Locally Convex Functions
AGGLIO: Global Optimization for Locally Convex Functions
Debojyoti Dey
B. Mukhoty
Purushottam Kar
14
2
0
06 Nov 2021
DAGs with No Curl: An Efficient DAG Structure Learning Approach
DAGs with No Curl: An Efficient DAG Structure Learning Approach
Yue Yu
Tian Gao
Naiyu Yin
Q. Ji
CML
30
59
0
14 Jun 2021
Learnable Embedding Sizes for Recommender Systems
Learnable Embedding Sizes for Recommender Systems
Siyi Liu
Chen Gao
Yihong Chen
Depeng Jin
Yong Li
61
83
0
19 Jan 2021
The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax
  Lower Bounds
The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds
T. Tony Cai
Yichen Wang
Linjun Zhang
FedML
43
20
0
08 Nov 2020
Best subset selection is robust against design dependence
Best subset selection is robust against design dependence
Yongyi Guo
Ziwei Zhu
Jianqing Fan
13
7
0
03 Jul 2020
Depth Descent Synchronization in $\mathrm{SO}(D)$
Depth Descent Synchronization in SO(D)\mathrm{SO}(D)SO(D)
Tyler Maunu
Gilad Lerman
MDE
37
2
0
13 Feb 2020
Stochastic Iterative Hard Thresholding for Graph-structured Sparsity
  Optimization
Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization
Baojian Zhou
F. Chen
Yiming Ying
29
7
0
09 May 2019
High Dimensional Robust $M$-Estimation: Arbitrary Corruption and Heavy
  Tails
High Dimensional Robust MMM-Estimation: Arbitrary Corruption and Heavy Tails
L. Liu
Tianyang Li
C. Caramanis
21
14
0
24 Jan 2019
Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints,
  High-Dimensionality and Saddle-Points
Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints, High-Dimensionality and Saddle-Points
Krishnakumar Balasubramanian
Saeed Ghadimi
ODL
14
100
0
17 Sep 2018
MISSION: Ultra Large-Scale Feature Selection using Count-Sketches
MISSION: Ultra Large-Scale Feature Selection using Count-Sketches
Amirali Aghazadeh
Ryan Spring
Daniel LeJeune
Gautam Dasarathy
Anshumali Shrivastava
Richard G. Baraniuk
10
32
0
12 Jun 2018
High Dimensional Robust Sparse Regression
High Dimensional Robust Sparse Regression
L. Liu
Yanyao Shen
Tianyang Li
C. Caramanis
12
71
0
29 May 2018
Non-convex Optimization for Machine Learning
Non-convex Optimization for Machine Learning
Prateek Jain
Purushottam Kar
33
479
0
21 Dec 2017
A Well-Tempered Landscape for Non-convex Robust Subspace Recovery
A Well-Tempered Landscape for Non-convex Robust Subspace Recovery
Tyler Maunu
Teng Zhang
Gilad Lerman
24
63
0
13 Jun 2017
Guarantees for Greedy Maximization of Non-submodular Functions with
  Applications
Guarantees for Greedy Maximization of Non-submodular Functions with Applications
Yatao Bian
J. M. Buhmann
Andreas Krause
Sebastian Tschiatschek
23
236
0
06 Mar 2017
Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to
  Non-smooth Concave Maximization
Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization
Bo Liu
Xiaotong Yuan
Lezi Wang
Qingshan Liu
Dimitris N. Metaxas
18
16
0
01 Mar 2017
On Context-Dependent Clustering of Bandits
On Context-Dependent Clustering of Bandits
Claudio Gentile
Shuai Li
Purushottam Kar
Alexandros Karatzoglou
Evans Etrue
Giovanni Zappella
15
138
0
06 Aug 2016
Fast Algorithms for Demixing Sparse Signals from Nonlinear Observations
Fast Algorithms for Demixing Sparse Signals from Nonlinear Observations
Mohammadreza Soltani
C. Hegde
27
29
0
03 Aug 2016
Nearly-optimal Robust Matrix Completion
Nearly-optimal Robust Matrix Completion
Yeshwanth Cherapanamjeri
Kartik Gupta
Prateek Jain
41
100
0
23 Jun 2016
Stochastic gradient descent methods for estimation with large data sets
Stochastic gradient descent methods for estimation with large data sets
Dustin Tran
Panos Toulis
E. Airoldi
12
14
0
22 Sep 2015
Optimal Rates of Convergence for Noisy Sparse Phase Retrieval via
  Thresholded Wirtinger Flow
Optimal Rates of Convergence for Noisy Sparse Phase Retrieval via Thresholded Wirtinger Flow
T. Tony Cai
Xiaodong Li
Zongming Ma
29
232
0
10 Jun 2015
Robust Regression via Hard Thresholding
Robust Regression via Hard Thresholding
Kush S. Bhatia
Prateek Jain
Purushottam Kar
AAML
OOD
13
156
0
08 Jun 2015
Convergence radius and sample complexity of ITKM algorithms for
  dictionary learning
Convergence radius and sample complexity of ITKM algorithms for dictionary learning
Karin Schnass
38
39
0
24 Mar 2015
Fast, Robust and Non-convex Subspace Recovery
Fast, Robust and Non-convex Subspace Recovery
Gilad Lerman
Tyler Maunu
38
77
0
24 Jun 2014
1