The challenge of learning a new concept, object, or a new medical disease recognition
without receiving any examples beforehand is called Zero-Shot Learning (ZSL). One of the …

由于侧视和相干成像机制, 当高分辨率合成孔径雷达(SAR) 图像的成像视角变化较大时,
图像间的特征差异会变大, 使图像配准难度增加. 针对高分辨率多视角SAR 图像 …

Successful data representation is a fundamental factor in machine learning based medical
imaging analysis. Deep Learning (DL) has taken an essential role in robust representation …

Increasingly many real world tasks involve data in multiple modalities or views. This has
motivated the development of many effective algorithms for learning a common latent space …

Successful data representation is a fundamental factor in machine learning based medical
imaging analysis. Deep Learning (DL) has taken an essential role in robust representation …

Word translation, or bilingual dictionary induction, is an important capability that impacts
many multilingual language processing tasks. Recent research has shown that word …

Aiming at the structural learning problem of the additive noise model in causal discovery and
the challenge of massive data processing in the era of artificial intelligence, this paper …

Estimating mutual information is an important statistics and machine learning problem. To
estimate the mutual information from data, a common practice is preparing a set of paired …

In this paper, we propose a novel semisupervised learning framework to learn the flows of
edges over a graph. Given the flow values of the labeled edges, the task of this paper is to …

In this work, we explore the problem of aligning two time-ordered point clouds which are
spatially transformed and re-parameterized versions of each other. This has a diverse array …