Summary of Safe Semi-supervised Contrastive Learning Using In-distribution Data As Positive Examples, by Min Gu Kwak et al.
Safe Semi-Supervised Contrastive Learning Using In-Distribution Data as Positive Examplesby Min Gu Kwak, Hyungu Kahng,…
Safe Semi-Supervised Contrastive Learning Using In-Distribution Data as Positive Examplesby Min Gu Kwak, Hyungu Kahng,…
Image Clustering Algorithm Based on Self-Supervised Pretrained Models and Latent Feature Distribution Optimizationby Qiuyu Zhu,…
Unsupervised Representation Learning by Balanced Self Attention Matchingby Daniel Shalam, Simon KormanFirst submitted to arxiv…
You Can’t Ignore Either: Unifying Structure and Feature Denoising for Robust Graph Learningby Tianmeng Yang,…
Mobility-Aware Federated Self-supervised Learning in Vehicular Networkby Xueying Gu, Qiong Wu, Pingyi Fan, Qiang FanFirst…
EUDA: An Efficient Unsupervised Domain Adaptation via Self-Supervised Vision Transformerby Ali Abedi, Q. M. Jonathan…
ELP-Adapters: Parameter Efficient Adapter Tuning for Various Speech Processing Tasksby Nakamasa Inoue, Shinta Otake, Takumi…
Accelerating Large Language Model Inference with Self-Supervised Early Exitsby Florian ValadeFirst submitted to arxiv on:…
Dense Self-Supervised Learning for Medical Image Segmentationby Maxime Seince, Loic Le Folgoc, Luiz Augusto Facury…
A Large Encoder-Decoder Family of Foundation Models For Chemical Languageby Eduardo Soares, Victor Shirasuna, Emilio…