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Minseok Kim

11 papers hereh-index 163.6k citations27 works total

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

author position
  • first author2
  • middle author9

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.LG5
  • eess.AS4
  • cs.IR1
  • cs.SD1
same name
  • Minseok Kim — 9 papers, h 15
  • Minseok Kim — 6 papers, h 4
  • Minseok Kim — 6 papers, h 5
  • Minseok Kim — 5 papers, h 3
  • Minseok Kim — 5 papers, h 3
  • Minseok Kim — 5 papers, h 2

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
20192023
most citedLearning from Noisy Labels with Deep Neural Networks: A Survey

91 citations · 255 across the 11 of their papers we have counts for

collaborators
Showing 2019Show all

3 papers · 1 filter

eess.AS2019★ 25 cited

Investigating U-Nets with various Intermediate Blocks for Spectrogram-based Singing Voice Separation

Woosung Choi, Minseok Kim, Jaehwa Chung +2

Singing Voice Separation (SVS) tries to separate singing voice from a given mixed musical signal. Recently, many U-Net-based models have been proposed for the SVS task, but there w…

cs.LG2019★ 18 cited

How does Early Stopping Help Generalization against Label Noise?

Hwanjun Song, Minseok Kim, Dongmin Park +1

Noisy labels are very common in real-world training data, which lead to poor generalization on test data because of overfitting to the noisy labels. In this paper, we claim that su…

cs.LG2019

Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive Batch Selection

Hwanjun Song, Minseok Kim, Sundong Kim +1

The accuracy of deep neural networks is significantly affected by how well mini-batches are constructed during the training step. In this paper, we propose a novel adaptive batch s…

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