Showing results 1 to 6 of 6
Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning Kim, Sungnyun; Bae, Sangmin; Yun, Seyoung, The IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023, pp.7537 - 7547, IEEE/CVF, 2023-06-20 |
Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding Bae, Sangmin; Ko, Jongwoo; Song, Hwanjun; Yun, Seyoung, The 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP, 2023-12-09 |
Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification Bae, Sangmin; Kim, June-Woo; Cho, Won-Yang; Baek, Hyerim; Son, Soyoun; Lee, Byungjo; Ha, Changwan; et al, 24th International Speech Communication Association, Interspeech 2023, pp.5436 - 5440, International Speech Communication Association, 2023-08-22 |
Preservation of the Global Knowledge by Not-True Distillation in Federated Learning Lee, Gihun; Jeong, Minchan; Shin, Yongjin; Bae, Sangmin; Yun, Seyoung, 36th Conference on Neural Information Processing Systems, NeurIPS 2022, Advances in Neural Information Processing Systems (NeurIPS), 2022-11-30 |
Re-thinking Federated Active Learning based on Inter-class Diversity Kim, Sangmook; Bae, Sangmin; Song, Hwanjun; Yun, Seyoung, The IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023, pp.3944 - 3953, IEEE/CVF, 2023-06-20 |
Self-Contrastive Learning: Single-Viewed Supervised Contrastive Framework Using Sub-network Bae, Sangmin; Kim, Sungnyun; Ko, Jongwoo; Lee, Gihun; Noh, Seungjong; Yun, Seyoung, 37th AAAI Conference on Artificial Intelligence, AAAI 2023, pp.197 - 205, AAAI Press, 2023-02-10 |
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