목록전체 글 (46)
둔비의 공부공간
Learned step size quantization
블로그에 자세히 정리한다고 생각하고 글을 쓰다 보니, 논문 리뷰가 아니라 번역에 가깝게 옮겨놓게 되면서[작성중] 카테고리에 비공개로 쓰다가 만 논문들이 너무 많아졌다.그냥 한번 읽고, 기억나는 내용을 중점으로 정리하는 방법으로 바꿔야겠다. https://arxiv.org/abs/1902.08153 Learned Step Size QuantizationDeep networks run with low precision operations at inference time offer power and space advantages over high precision alternatives, but need to overcome the challenge of maintaining high accuracy as..
DaFKD: Domain-aware Federated Knowledge Distillation
https://openaccess.thecvf.com/content/CVPR2023/html/Wang_DaFKD_Domain-Aware_Federated_Knowledge_Distillation_CVPR_2023_paper.html CVPR 2023 Open Access RepositoryDaFKD: Domain-Aware Federated Knowledge Distillation Haozhao Wang, Yichen Li, Wenchao Xu, Ruixuan Li, Yufeng Zhan, Zhigang Zeng; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, pp. 20412-2..
Complement Sparsification: Low-Overhead Model Pruning for Federated Learning
Federated + Pruninghttps://arxiv.org/pdf/2303.06237 AAAI 2023 Accepted *communication cost : Federated Learning에서 server와 client간의 통신에서 발생하는 overhead를 말한다. AbstractFederated Learning은 privacy-preserving distributed deep learning paradigm이다.하지만, Federated Learning은 computation과 communucation cost가 필요하기 때문에 특히 mobile같은 환경의 장비에겐 부담된다. 기존 Pruning 방법들은 client server간의 낮은 양방향 communication cost, clie..
Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning
https://openreview.net/forum?id=Y9t7MqZtCR Sparse Weight Averaging with Multiple Particles for Iterative...Given the ever-increasing size of modern neural networks, the significance of sparse architectures has surged due to their accelerated inference speeds and minimal memory demands. When it comes to...openreview.net(재구현이 되는지는 검증하지 못했는데, 위 링크에 zip파일에 보면 코드도 올라와있다.) AbstractIMP(Iterative Magni..