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Sangmin Bae

3 papers here

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

author position
  • middle author3

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

fields
  • cs.LG2
  • cs.CV1

identity via Semantic Scholar / OpenAlex

most citedMixCo: Mix-up Contrastive Learning for Visual Representation

53 citations · 58 across the 2 of their papers we have counts for

collaborators

3 papers

cs.LG2020★ 5 cited

Accurate and Fast Federated Learning via Combinatorial Multi-Armed Bandits

Taehyeon Kim, Sangmin Bae, Jin-woo Lee +1

Federated learning has emerged as an innovative paradigm of collaborative machine learning. Unlike conventional machine learning, a global model is collaboratively learned while da…

cs.CV2020★ 53 cited

MixCo: Mix-up Contrastive Learning for Visual Representation

Sungnyun Kim, Gihun Lee, Sangmin Bae +1

Contrastive learning has shown remarkable results in recent self-supervised approaches for visual representation. By learning to contrast positive pairs' representation from the co…

cs.LG2020

SIPA: A Simple Framework for Efficient Networks

Gihun Lee, Sangmin Bae, Jaehoon Oh +1

With the success of deep learning in various fields and the advent of numerous Internet of Things (IoT) devices, it is essential to lighten models suitable for low-power devices. I…

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