This project is going to develop novel learning systems and learning algorithms for multi-task learning in terms of different learning paradigms ranging from supervised, unsupervised to reinforcement learning and their applications to real world problems. The main research theme is how to share the gen...
We employ state-of-the-art techniques from learning to 1) find a suitable similarity function for each view, and 2) compare different multi-view learning techniques to decompose a software system into high-level units and give component-level recommendations for refactoring of the system, as ...
Multiview Learning in Biomedical Applicationsdoi:10.1016/B978-0-12-815480-9.00013-XAngela SerraPaola GaldiRoberto Tagliaferri
14.1 N19 Multiview Boosting by Controlling the Diversity and the Accuracy of View-specific Voters(python) 15.1 arXiv21 Multi-view Data Visualisation via Manifold Learning(python) Part B: multi-view applications with code 1. Incomplete or partial multi-view learning ...
论文阅读:Deep multi-view learning methods: A review 因为方向原因,这里主要是其中的GNN部分 a b s t r a c t 多视点学习(MVL)通过利用多个特征或模式的互补信息,受到越来越多的关注,并取得了巨大的实践成功。近年来,由于深层模型的显著性能,深层MVL在机器学习、人工智能和计算机视觉等领域得到了广泛的应用。
1. This linear nature of multi-view data make the learning task on multi-view data remain still challenging. Recently, due to the powerful feature abstraction ability, deep learning methods [31] have vast inroads into many applications with outstanding performance, such as computer vision [20],...
整体上来说,主要的创新包括两点:首先是使用一个编码器生成两个嵌入向量,区分了view-common和view-specific两种表示,其次此基础上引入了一个视图分类器,形成了对抗的视图学习过程。思想上的创新大于技术上的创新。所谓自适应的权重向量学习,讲了一大堆,最后融合成了一个。且 ...
years,multi-view learning has provoked vast amount of attention and research.This paper surveys the research progress of multi-view learning and introduces its own works and the applications.Furthermore,it points out the challenges and suggests the future research direction of multi-view learning. ...
Few-Shot Food Recognition via Multi-View Representation Learning This article considers the problem of few-shot learning for food recognition. Automatic food recognition can support various applications, e.g., dietary as... S Jiang,W Min,Y Lv,... - 《Acm Transactions on Multimedia Computing Com...
Here we propose COMEBin, a contig binning method based on contrastive multi-view representation learning. The key contributions of COMEBin can be summarized as follows: 1) We introduce a data augmentation approach that generates multiple views for each contig, enabling contrastive learning and yieldin...