In this paper, we propose a novel algorithm, i.e., Latent Semantics Encoding for Label Distribution Learning (LSE-LDL), which learns the label distribution and ...
In this paper, we propose a novel algorithm, i.e., Latent Semantics Encoding for Label Distribution Learning (LSE-LDL), which learns the label distribution and ...
This paper designs an efficient recovery model to recover the latent label distributions of training instances, named Fast Label Enhancement (FLE), ...
Aug 10, 2019 · In this paper, we propose a novel algorithm, i.e., Latent Semantics Encoding for Label Distribution Learning (LSE-LDL), which learns the label ...
Jun 23, 2019 · In this paper, we propose a novel algorithm, i.e., Latent Semantics Encoding for Label Distribution Learning (LSE-LDL), which learns the label ...
标签分布学习的潜在语义编码（LSE-LDL），它在潜在语义的指导下学习标签分布并同时实现特征选择。 具体地说，为了减轻噪声干扰，我们寻求并编码有区别的原始物理/化学特征 ...
Sep 28, 2022 · The first part starts with a latent feature predic- tion stream (SNN with an MLP) that learns the input information to predict the feature maps.
To reduce feature noise, latent semantics encoding for LDL (LSE-LDL) Xu et al. (2019) converts the original data features into latent semantic features, and ...
People also ask
What is latent semantic analysis an approach to understand semantic of text?
What is label distribution learning?
Label distribution learning (LDL) is a generalized machine learning framework for dealing with label ambiguity, as it can explore the relative importance ...
Dec 9, 2024 · Our basic idea is that the underlying manifold structure of label distribution may encode the correlations among labels. LDL-LDM works as ...