通过·米塞斯-菲舍尔超球嵌入,用于多视图聚类的脱的表示学习
Zhixiang Li1, Zhiwen Luo2, Nizar Bouguila2
1Hong Kong Baptist University, 999077, Hong Kong Special Administrative Region of China; Guangdong Provincial/Zhuhai Key Laboratory IRADS and Department of Computer Science, Beijing Normal-Hong Kong Baptist University, Zhuhai, 519087, Guangdong, China.
概括
本研究引入了一种使用超球嵌入和·米塞斯-菲舍尔分布的新对比的多视图集群方法. 该方法增强了复杂,高维数据集的数据对齐和信息融合.
科学领域:
- 机器学习 机器学习
- 数据科学数据科学数据科学
- 计算统计学 计算统计学
背景情况:
- 多视图集群集成了多样化的数据,但往往假定高斯隐藏空间,限制了复杂的高维数据的性能.
- 由于非高斯分布,现有的方法在数据对齐,信息融合和相似度测量方面遇到了困难.
研究的目的:
- 提出一种新的对比的多视图集群框架,解决潜伏空间中高斯假设的局限性.
- 改进复杂数据集的数据对齐,信息融合和相似性测量.
主要方法:
- 开发了一个使用模拟von Mises-Fisher (vMF) 分布的超球嵌入的框架.
- 纳入了对比式学习范式,对歧视性表示进行了对齐和统一性损失.
- 在多个视图中优化集群内部凝聚力和集群间分离能力.
主要成果:
- 拟议的方法显著优于对基准数据集的最先进方法.
- 展示了卓越的性能,特别是在高维和复杂的非高斯数据分布.
- 实现了加强集群内部凝聚力和集群间分离能力.
结论:
- 超球嵌入方法与vMF分布和对比学习有效地处理复杂的多视图数据.
- 该框架为多视图集群挑战提供了强大的解决方案,改善了表示学习和集群准确性.
- 公开可用的代码有助于可重复性和进一步研究.
相关概念视频
Fischer Projections
13.9K
Learning to draw Fischer projections of molecules and understanding their relevance plays a crucial role in the visual depiction of organic molecules. A Fischer projection is a two-dimensional projection on a planar surface to simplify the three-dimensional wedge–dash representation of molecules. This is especially helpful in the case of molecules with multiple chiral centers that can be difficult to draw. Here, all the bonds of interest are represented as horizontal or vertical lines.
13.9K
Collisions in Multiple Dimensions: Introduction
5.6K
It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
5.6K
Collisions in Multiple Dimensions: Problem Solving
4.4K
In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
4.4K
Multicompartment Models: Overview
258
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
258
Cluster Sampling Method
12.8K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
12.8K
Cartesian Form for Vector Formulation
758
The Cartesian form for vector formulation is a process to calculate the moment of force using the position and force vectors. The moment of force is defined as the cross-product of these vectors, making it a vector quantity. The Cartesian form of the position and force vectors involves unit vectors, which can be used to express the cross-product in determinant form.
758


