Cha, Sungmin

22 publications

ICLRW 2025 Cost-Efficient Continual Learning with Sufficient Exemplar Memory Dong Kyu Cho, Taesup Moon, Rumi Chunara, Kyunghyun Cho, Sungmin Cha

TMLR 2025 Hyperparameters in Continual Learning: A Reality Check Sungmin Cha, Kyunghyun Cho

ICLR 2025 Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMs Sungmin Cha, Sungjun Cho, Dasol Hwang, Moontae Lee

NeurIPS 2025 Why Knowledge Distillation Works in Generative Models: A Minimal Working Explanation Sungmin Cha, Kyunghyun Cho

AAAI 2024 Learning to Unlearn: Instance-Wise Unlearning for Pre-Trained Classifiers Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee

WACV 2024 NCIS: Neural Contextual Iterative Smoothing for Purifying Adversarial Perturbations Sungmin Cha, Naeun Ko, Heewoong Choi, Youngjoon Yoo, Taesup Moon

ICML 2024 Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning Sungmin Cha, Kyunghyun Cho, Taesup Moon

ECCV 2024 Salience-Based Adaptive Masking: Revisiting Token Dynamics for Enhanced Pre-Training Hyesong Choi, Hyejin Park, Kwang Moo Yi, Sungmin Cha, Dongbo Min

CoLLAs 2024 Towards More Diverse Evaluation of Class Incremental Learning: Representation Learning Perspective Sungmin Cha, Jihwan Kwak, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon

CoLLAs 2024 Towards Realistic Incremental Scenario in Class Incremental Semantic Segmentation Jihwan Kwak, Sungmin Cha, Taesup Moon

NeurIPSW 2024 Towards Robust and Cost-Efficient Knowledge Unlearning for Large Language Models Sungmin Cha, Sungjun Cho, Dasol Hwang, Moontae Lee

CVPR 2023 Rebalancing Batch Normalization for Exemplar-Based Class-Incremental Learning Sungmin Cha, Sungjun Cho, Dasol Hwang, Sunwon Hong, Moontae Lee, Taesup Moon

ICLR 2021 CPR: Classifier-Projection Regularization for Continual Learning Sungmin Cha, Hsiang Hsu, Taebaek Hwang, Flavio Calmon, Taesup Moon

CVPR 2021 FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise Jaeseok Byun, Sungmin Cha, Taesup Moon

ICLR 2021 GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images Sungmin Cha, Taeeon Park, Byeongjoon Kim, Jongduk Baek, Taesup Moon

NeurIPS 2021 SSUL: Semantic Segmentation with Unknown Label for Exemplar-Based Class-Incremental Learning Sungmin Cha, Beomyoung Kim, YoungJoon Yoo, Taesup Moon

ICMLW 2021 Self-Supervised Iterative Contextual Smoothing for Efficient Adversarial Defense Against Gray- and Black-Box Attack Sungmin Cha, Naeun Ko, YoungJoon Yoo, Taesup Moon

ICMLW 2020 CPR: Classifier-Projection Regularization for Continual Learning Sungmin Cha, Hsiang Hsu, Flavio du Pin Calmon, and Taesup Moon

NeurIPS 2020 Continual Learning with Node-Importance Based Adaptive Group Sparse Regularization Sangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup Moon

NeurIPSW 2020 GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images Sungmin Cha, Taeeon Park, Byeongjoon Kim, Jongduk Baek, Taesup Moon

AAAI 2019 DoPAMINE: Double-Sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling Sunghwan Joo, Sungmin Cha, Taesup Moon

NeurIPS 2019 Uncertainty-Based Continual Learning with Adaptive Regularization Hongjoon Ahn, Sungmin Cha, Donggyu Lee, Taesup Moon