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researcher

Jun Zhu

9 papers here

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

author position
  • sole author1
  • middle author3
  • last author5

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.LG5
  • stat.ML2
  • cs.AI1
  • cs.CV1
ORCID 0000-0002-6254-2388
same name
  • Jun Zhu — 107 papers, h 74
  • Jun Zhu — 32 papers, h 15
  • Jun Zhu — 26 papers, h 12
  • Jun Zhu — 20 papers, h 10
  • Jun Zhu — 16 papers, h 10
  • Jun Zhu — 14 papers, h 12

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
20122024
most citedMax-Margin Nonparametric Latent Feature Models for Link Prediction

37 citations · 121 across the 9 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2024★ 1 cited

ManiBox: Enhancing Embodied Spatial Generalization via Scalable Simulation Data Generations

Hengkai Tan, Xuezhou Xu, Chengyang Ying +7

Embodied agents require robust spatial intelligence to execute precise real-world manipulations. However, this remains a significant challenge, as current methods often struggle to…

cs.LG2014

Contrastive Feature Induction for Efficient Structure Learning of Conditional Random Fields

Ni Lao, Jun Zhu

Structure learning of Conditional Random Fields (CRFs) can be cast into an L1-regularized optimization problem. To avoid optimizing over a fully linked model, gain-based or gradien…

cs.LG2014★ 14 cited

Dropout Training for Support Vector Machines

Ning Chen, Jun Zhu, Jianfei Chen +1

Dropout and other feature noising schemes have shown promising results in controlling over-fitting by artificially corrupting the training data. Though extensive theoretical and em…

cs.LG2012★ 37 cited

Max-Margin Nonparametric Latent Feature Models for Link Prediction

Jun Zhu

We present a max-margin nonparametric latent feature model, which unites the ideas of max-margin learning and Bayesian nonparametrics to discover discriminative latent features for…

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