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researcher

T. Zhang

83 papers hereh-index 6621.4k citations717 works total

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

author position
  • sole author2
  • first author10
  • middle author29
  • last author39

Across the 80 of 83 papers where every author was matched, so the position is known.

fields
  • cs.CV21
  • cs.LG21
  • cs.CL12
  • cs.IT8
  • stat.ML8
  • math.OC4
same name
  • T. Zhang — 251 papers
  • T. Zhang — 84 papers, h 25
  • T. Zhang — 43 papers, h 65
  • T. Zhang — 22 papers, h 40
  • T. Zhang — 19 papers
  • T. Zhang — 16 papers, h 19

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
20132025
most citedSpatial-Temporal Recurrent Neural Network for Emotion Recognition

604 citations · 2k across the 82 of their papers we have counts for

collaborators
Showing 2014Show all

4 papers · 1 filter

cs.LG2014★ 1 cited

Adjusting Leverage Scores by Row Weighting: A Practical Approach to Coherent Matrix Completion

Shusen Wang, Tong Zhang, Zhihua Zhang

Low-rank matrix completion is an important problem with extensive real-world applications. When observations are uniformly sampled from the underlying matrix entries, existing meth…

cs.IT2014★ 5 cited

Joint Multi-Cell Resource Allocation Using Pure Binary-Integer Programming for LTE Uplink

Tong Zhang, Xiaofeng Tao, Qimei Cui

Due to high system capacity requirement, 3GPP Long Term Evolution (LTE) is likely to adopt frequency reuse factor 1 at the cost of suffering severe inter-cell interference (ICI). O…

stat.ML2014★ 84 cited

Accelerating Minibatch Stochastic Gradient Descent using Stratified Sampling

Peilin Zhao, Tong Zhang

Stochastic Gradient Descent (SGD) is a popular optimization method which has been applied to many important machine learning tasks such as Support Vector Machines and Deep Neural N…

stat.ML2014★ 62 cited

Stochastic Optimization with Importance Sampling

Peilin Zhao, Tong Zhang

Uniform sampling of training data has been commonly used in traditional stochastic optimization algorithms such as Proximal Stochastic Gradient Descent (prox-SGD) and Proximal Stoc…

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