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Jungwuk Park

3 papers here

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

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG3

identity via Semantic Scholar / OpenAlex

most citedNEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks

3 citations · 5 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2024

Consistency-Guided Temperature Scaling Using Style and Content Information for Out-of-Domain Calibration

Wonjeong Choi, Jungwuk Park, Dong-Jun Han +2

Research interests in the robustness of deep neural networks against domain shifts have been rapidly increasing in recent years. Most existing works, however, focus on improving th…

cs.LG2023★ 3 cited

NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks

Seokil Ham, Jungwuk Park, Dong-Jun Han +1

While multi-exit neural networks are regarded as a promising solution for making efficient inference via early exits, combating adversarial attacks remains a challenging problem. I…

cs.LG2023★ 2 cited

StableFDG: Style and Attention Based Learning for Federated Domain Generalization

Jungwuk Park, Dong-Jun Han, Jinho Kim +3

Traditional federated learning (FL) algorithms operate under the assumption that the data distributions at training (source domains) and testing (target domain) are the same. The f…

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