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Bo Zhang

6 papers hereh-index 230 citations6 works total

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

author position
  • middle author2
  • last author4

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • math.OC1
  • math.ST1
same name
  • Bo Zhang — 39 papers, h 28
  • Bo Zhang — 20 papers, h 27
  • Bo Zhang — 18 papers
  • Bo Zhang — 14 papers, h 19
  • Bo Zhang — 13 papers
  • Bo Zhang — 13 papers

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
20192025
most citedRealization of spatial sparseness by deep ReLU nets with massive data

2 citations · 2 across the 4 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2025

Online AUC Optimization Based on Second-order Surrogate Loss

JunRu Luo, Difei Cheng, Bo Zhang

The Area Under the Curve (AUC) is an important performance metric for classification tasks, particularly in class-imbalanced scenarios. However, minimizing the AUC presents signifi…

cs.LG2025

Stochastic Gradient Descent in Non-Convex Problems: Asymptotic Convergence with Relaxed Step-Size via Stopping Time Methods

Ruinan Jin, Difei Cheng, Hong Qiao +3

Stochastic Gradient Descent (SGD) is widely used in machine learning research. Previous convergence analyses of SGD under the vanishing step-size setting typically require Robbins-…

cs.LG2024

Exploring and Exploiting the Asymmetric Valley of Deep Neural Networks

Xin-Chun Li, Jin-Lin Tang, Bo Zhang +2

Exploring the loss landscape offers insights into the inherent principles of deep neural networks (DNNs). Recent work suggests an additional asymmetry of the valley beyond the flat…

cs.LG2019★ 2 cited

Realization of spatial sparseness by deep ReLU nets with massive data

Charles K. Chui, Shao-Bo Lin, Bo Zhang +1

The great success of deep learning poses urgent challenges for understanding its working mechanism and rationality. The depth, structure, and massive size of the data are recognize…

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