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. 1511.03766
  4. Cited By
Sparse Learning for Large-scale and High-dimensional Data: A Randomized
  Convex-concave Optimization Approach
v1v2 (latest)

Sparse Learning for Large-scale and High-dimensional Data: A Randomized Convex-concave Optimization Approach

12 November 2015
Lijun Zhang
Tianbao Yang
Rong Jin
Zhi Zhou
ArXiv (abs)PDFHTML

Papers citing "Sparse Learning for Large-scale and High-dimensional Data: A Randomized Convex-concave Optimization Approach"

3 / 3 papers shown
Title
Sketching for Convex and Nonconvex Regularized Least Squares with Sharp
  Guarantees
Sketching for Convex and Nonconvex Regularized Least Squares with Sharp Guarantees
Yingzhen Yang
Ping Li
34
0
0
03 Nov 2023
Fast Low-rank Metric Learning for Large-scale and High-dimensional Data
Fast Low-rank Metric Learning for Large-scale and High-dimensional Data
Han Liu
Zhizhong Han
Yu-Shen Liu
M. Gu
109
7
0
13 Sep 2019
On the Suboptimality of Proximal Gradient Descent for $\ell^{0}$ Sparse
  Approximation
On the Suboptimality of Proximal Gradient Descent for ℓ0\ell^{0}ℓ0 Sparse Approximation
Yingzhen Yang
Jiashi Feng
Nebojsa Jojic
Jianchao Yang
Thomas S. Huang
17
3
0
05 Sep 2017
1