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Jie Shen

14 papers hereh-index 12462 citations29 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author3
  • first author4
  • middle author3
  • last author4

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.LG7
  • stat.ML4
  • cs.CV1
  • cs.DS1
  • cs.SI1
same name
  • Jie Shen — 31 papers, h 5
  • Jie Shen — 28 papers, h 19
  • Jie Shen — 25 papers, h 45
  • Jie Shen — 19 papers, h 83
  • Jie Shen — 19 papers, h 20
  • Jie Shen — 7 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20142023
most citedA Tight Bound of Hard Thresholding

58 citations · 89 across the 14 of their papers we have counts for

collaborators
Showing stat.MLShow all

4 papers · 1 filter

stat.ML2020★ 3 cited

Attribute-Efficient Learning of Halfspaces with Malicious Noise: Near-Optimal Label Complexity and Noise Tolerance

Jie Shen, Chicheng Zhang

This paper is concerned with computationally efficient learning of homogeneous sparse halfspaces in Rd under noise. Though recent works have established attribute-effic…

stat.ML2016★ 58 cited

A Tight Bound of Hard Thresholding

Jie Shen, Ping Li

This paper is concerned with the hard thresholding operator which sets all but the k largest absolute elements of a vector to zero. We establish a {\em tight} bound to quantitati…

stat.ML2015★ 2 cited

Efficient Online Minimization for Low-Rank Subspace Clustering

Jie Shen, Ping Li, Huan Xu

Low-rank representation~(LRR) has been a significant method for segmenting data that are generated from a union of subspaces. It is, however, known that solving the LRR program is…

stat.ML2014

Online Optimization for Large-Scale Max-Norm Regularization

Jie Shen, Huan Xu, Ping Li

Max-norm regularizer has been extensively studied in the last decade as it promotes an effective low-rank estimation for the underlying data. However, such max-norm regularized pro…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.