arXiv:2107.03690
Proceedings of the First Workshop on Weakly Supervised Learning (WeaSuL)
원문 초록
Welcome to WeaSuL 2021, the First Workshop on Weakly Supervised Learning, co-located with ICLR 2021. In this workshop, we want to advance theory, methods and tools for allowing experts to express prior coded knowledge for automatic data annotations that can be used to train arbitrary deep neural networks for prediction. The ICLR 2021 Workshop on Weak Supervision aims at advancing methods that help modern machine-learning methods to generalize from knowledge provided by experts, in interaction with observable (unlabeled) data. In total, 15 papers were accepted. All the accepted contributions are listed in these Proceedings.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Bootstrapping World Models from Dynamics Models in Multimodal Foundation Models
Partial Label Clustering
FG$^2$: Fine-Grained Cross-View Localization by Fine-Grained Feature Matching
QMaxViT-Unet+: A Query-Based MaxViT-Unet with Edge Enhancement for Scribble-Supervised Segmentation of Medical Images
ViSoLex: An Open-Source Repository for Vietnamese Social Media Lexical Normalization
HisynSeg: Weakly-Supervised Histopathological Image Segmentation via Image-Mixing Synthesis and Consistency Regularization
토론
이 논문과 연결된 포럼 글이 아직 없습니다.