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Sungmin Cha

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Sy-CON: Symmetric Contrastive Loss for Continual Self-Supervised Representation Learning

Jun 08, 2023
Sungmin Cha, Taesup Moon

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Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers

Jan 27, 2023
Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee

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Knowledge Unlearning for Mitigating Privacy Risks in Language Models

Oct 04, 2022
Joel Jang, Dongkeun Yoon, Sohee Yang, Sungmin Cha, Moontae Lee, Lajanugen Logeswaran, Minjoon Seo

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Is Continual Learning Truly Learning Representations Continually?

Jun 16, 2022
Sungmin Cha, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon

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Task-Balanced Batch Normalization for Exemplar-based Class-Incremental Learning

Jan 29, 2022
Sungmin Cha, Soonwon Hong, Moontae Lee, Taesup Moon

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Supervised Neural Discrete Universal Denoiser for Adaptive Denoising

Nov 24, 2021
Sungmin Cha, Seonwoo Min, Sungroh Yoon, Taesup Moon

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Observations on K-image Expansion of Image-Mixing Augmentation for Classification

Oct 08, 2021
Joonhyun Jeong, Sungmin Cha, Youngjoon Yoo, Sangdoo Yun, Taesup Moon, Jongwon Choi

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SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning

Jul 01, 2021
Sungmin Cha, Beomyoung Kim, Youngjoon Yoo, Taesup Moon

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Self-Supervised Iterative Contextual Smoothing for Efficient Adversarial Defense against Gray- and Black-Box Attack

Jun 22, 2021
Sungmin Cha, Naeun Ko, Youngjoon Yoo, Taesup Moon

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FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise

May 23, 2021
Jaeseok Byun, Sungmin Cha, Taesup Moon

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