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Jingwei Zhang

16 papers hereh-index 8276 citations21 works total

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

author position
  • first author9
  • middle author5
  • last author1

Across the 15 of 16 papers where every author was matched, so the position is known.

fields
  • cs.LG7
  • stat.ML6
  • cs.CV2
  • cs.CL1
same name
  • Jingwei Zhang — 19 papers, h 14
  • Jingwei Zhang — 12 papers, h 9
  • Jingwei Zhang — 5 papers, h 6
  • Jingwei Zhang — 4 papers, h 3
  • Jingwei Zhang — 3 papers, h 4
  • Jingwei Zhang — 3 papers, h 3

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
20182026
most citedTheoretical Analysis of Adversarial Learning: A Minimax Approach

28 citations · 70 across the 16 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

stat.ML2018★ 4 cited

An Optimal Transport View on Generalization

Jingwei Zhang, Tongliang Liu, Dacheng Tao

We derive upper bounds on the generalization error of learning algorithms based on their \emph{algorithmic transport cost}: the expected Wasserstein distance between the output hyp…

stat.ML2018★ 28 cited

Theoretical Analysis of Adversarial Learning: A Minimax Approach

Zhuozhuo Tu, Jingwei Zhang, Dacheng Tao

Here we propose a general theoretical method for analyzing the risk bound in the presence of adversaries. Specifically, we try to fit the adversarial learning problem into the mini…

stat.ML2018★ 21 cited

An Information-Theoretic View for Deep Learning

Jingwei Zhang, Tongliang Liu, Dacheng Tao

Deep learning has transformed computer vision, natural language processing, and speech recognition\cite{badrinarayanan2017segnet, dong2016image, ren2017faster, ji20133d}. However,…

stat.ML2018★ 2 cited

On the Rates of Convergence from Surrogate Risk Minimizers to the Bayes Optimal Classifier

Jingwei Zhang, Tongliang Liu, Dacheng Tao

We study the rates of convergence from empirical surrogate risk minimizers to the Bayes optimal classifier. Specifically, we introduce the notion of \emph{consistency intensity} to…

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