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Zhen Qin

28 papers hereh-index 12310 citations44 works total

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

author position
  • sole author4
  • first author18
  • middle author5

Across the 27 of 28 papers where every author was matched, so the position is known.

fields
  • quant-ph13
  • cs.LG8
  • eess.SP3
  • math.OC2
  • cs.IT1
  • stat.ML1
Homepage
same name
  • Zhen Qin — 25 papers, h 15
  • Zhen Qin — 22 papers, h 18
  • Zhen Qin — 13 papers, h 40
  • Zhen Qin — 13 papers, h 4
  • Zhen Qin — 13 papers, h 7
  • Zhen Qin — 10 papers, h 4

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
20222026
most citedQuantum State Tomography for Matrix Product Density Operators

15 citations · 28 across the 26 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

eess.SP2022

Proportionate Recursive Maximum Correntropy Criterion Adaptive Filtering Algorithms and their Performance Analysis

Zhen Qin, Jun Tao, Le Yang +1

The maximum correntropy criterion (MCC) has been employed to design outlier-robust adaptive filtering algorithms, among which the recursive MCC (RMCC) algorithm is a typical one. M…

math.OC2022★ 3 cited

A Validation Approach to Over-parameterized Matrix and Image Recovery

Lijun Ding, Zhen Qin, Liwei Jiang +2

This paper studies the problem of recovering a low-rank matrix from several noisy random linear measurements. We consider the setting where the rank of the ground-truth matrix is u…

quant-ph2022★ 6 cited

Quantum state tomography with tensor train cross approximation

Alexander Lidiak, Casey Jameson, Zhen Qin +4

It has been recently shown that a state generated by a one-dimensional noisy quantum computer is well approximated by a matrix product operator with a finite bond dimension indepen…

cs.LG2022★ 3 cited

Error Analysis of Tensor-Train Cross Approximation

Zhen Qin, Alexander Lidiak, Zhexuan Gong +3

Tensor train decomposition is widely used in machine learning and quantum physics due to its concise representation of high-dimensional tensors, overcoming the curse of dimensional…

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